hypothesis examples about sleep

August 1, 2013

12 min read

New Hypothesis Explains Why We Sleep

During sleep, the brain weakens the connections among nerve cells, apparently conserving energy and, paradoxically, aiding memory

By Giulio Tononi & Chiara Cirelli

Every night, while we lie asleep, blind, dumb and almost paralyzed, our brains are hard at work. Neurons in the sleeping brain fire nearly as often as they do in a waking state, and they consume almost as much energy. What is the point of this unceasing activity at a time when we are supposedly resting? Why does the conscious mind disconnect so completely from the external environment while the brain keeps nattering on?

The brain's activity during rest likely serves some essential function. The evidence for this importance starts with sleep's ubiquity. All animals apparently sleep even though being unconscious and unresponsive greatly raises the risk of becoming another creature's lunch. Birds do it, bees do it, iguanas and cockroaches do it, even fruit flies do it, as we and others demonstrated more than a decade ago.

Furthermore, evolution has devised a few extraordinary adaptations to accommodate sleep: dolphins and some other marine mammals that must surface often to breathe, for example, sleep by alternately switching off one hemisphere of their brain while the other remains in a waking state.

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Like many scientists and nonscientists, the two of us have long wondered what benefit sleep provides that makes it so crucial to living creatures. More than 20 years ago, when we worked together at the Sant'Anna School of Advanced Studies in Pisa, Italy, we began to suspect that the brain's activity during slumber may somehow restore to a baseline state the billions of neural connections that get modified every day by the events of waking life. Sleep, in this telling, would preserve the ability of the brain's circuitry to form new memories continually over the course of an individual's lifetime without becoming oversaturated or obliterating older memories.

We also have an idea of why awareness of the external environment must be shut off during sleep. It seems to us that conscious experience of the here and now has to be interrupted for the brain to gain the chance to integrate new and old memories; sleep provides that respite.

Our hypothesis is somewhat controversial among our fellow neuroscientists who study sleep's role in learning and memory because we suggest that the return to baseline results from a weakening of the links among the neurons that fire during sleep. Conventional wisdom holds, instead, that brain activity during sleep strengthens the neural connections involved in storing newly formed memories. Yet years of research with organisms ranging from flies to people lend support to our notions.

School of Nod

Scientists first proposed the idea that sleep is important to memory nearly a century ago, and plenty of experiments since then have shown that after a night of sleep, and sometimes just a nap, newly formed memories “stick” better than they would if one had spent the same amount of time awake. This pattern holds for declarative memories, such as lists of words and associations between pictures and places, as well as for procedural memories, which underlie perceptual and motor skills, such as playing a musical instrument.

The evidence that sleep benefits memory led scientists to look for signs that the brain rehashes newly learned material at night. They found them: studies performed over the past 20 years, first in rodents and then in humans, show that patterns of neural activity during sleep sometimes do resemble those recorded while subjects are awake. For example, when a rat learns to navigate a maze, certain neurons in a part of the brain called the hippocampus fire in specific sequences. During subsequent sleep, rats “replay” these sequences more often than predicted by chance.

Because of such findings, many researchers came to assume that sleep “replay” consolidates memories by further reinforcing synapses—the contact points between neurons—that have been strengthened when an individual is awake. The idea is that, as linked neurons fire repeatedly, the synapses connecting them more readily convey signals from one neuron to another, helping neuronal circuits to encode memories in the brain. This process of selective strengthening is known as synaptic potentiation, and it is the favored mechanism by which the brain is thought to accomplish learning and remembering.

Yet while replay and potentiation are known to occur during waking activities, scientists have so far found no direct evidence that the synapses in replayed circuits get strengthened during sleep. This lack of evidence hardly surprises us. It is consistent with our suspicion that while the sleeper lies unaware, all that brain activity—the “replay” as well as other, seemingly random firings—might actually be weakening neural connections, not strengthening them.

The Price of Plasticity

There are many good reasons to propose that synapses must become weakened as well as strengthened for the brain to function properly. For one thing, strong synapses consume more energy than weak ones, and the brain does not have infinite stores of energy. In humans the brain accounts for almost 20 percent of the body's energy budget—more than any other organ by weight—and at least two thirds of that portion goes to supporting synaptic activity. Building and bolstering synapses is also a major source of cellular stress, requiring cells to synthesize and deliver components ranging from mitochondria (the cell's power plants), to synaptic vesicles (which ferry signaling molecules), to various proteins and lipids that are needed for communication across synapses.

It seems clear to us that this strain on resources is unsustainable. The brain cannot go on strengthening and maintaining revved-up synapses both day and night for the whole of an individual's lifetime. We do not doubt that learning occurs mainly through synaptic potentiation. We simply doubt that strengthening continues to happen during sleep.

In contrast, synaptic weakening during sleep would restore brain circuitry to a baseline level of strength, thereby avoiding excessive energy consumption and cellular stress. We refer to this baseline-restoring function of sleep as preserving synaptic homeostasis, and we call our overall hypothesis about the role of sleep the synaptic homeostasis hypothesis, or SHY. In principle, SHY explains the essential, universal purpose of sleep for all organisms that do it: sleep restores the brain to a state where it can learn and adapt when we are awake. The risk we take by becoming disconnected from the environment for hours at a time is the price we pay for this neural recalibration. Most generally, sleep is the price we pay for the brain's plasticity—its ability to modify its wiring in response to experience.

But how does SHY explain sleep's salutary effects on learning and memory? How can weakened synapses improve the overall retention of skills and facts? Consider that, over the course of a typical day, almost everything you experience leaves a neural trace in the brain and that the significant events, like meeting a new person or learning a piece of music on the guitar, make up just a trifling portion of that neural encoding. To improve memory, the sleeping brain must somehow distinguish the “noise” of irrelevant information from the “signal” of significant happenings.

We suggest that in sleep, the spontaneous firing of neurons in the brain activates many different circuits in many different combinations, encompassing both new memory traces and old networks of learned associations. (You get a glimpse of this neural free-for-all in dreams.) The spontaneous activity lets the brain try out which new memories fit better with stored memories of proved significance and weakens those synapses that do not fit well in the grand scheme of memory. We and other investigators are exploring possible mechanisms by which brain activity could selectively weaken synapses that encode the “noise” while preserving those that correspond to the “signal.”

While the brain tries out these imaginary scenarios and enacts weakening where appropriate, we had best be unaware of the surrounding environment and be incapable of acting in it; that is, we had best be asleep. Likewise, restoring synaptic homeostasis should not take place while we are awake because the events of the day would dominate the process, giving salience to them rather than to all the knowledge the brain has accumulated over a lifetime. The profound disconnection of sleep frees our brain from the tyranny of the present, creating an ideal circumstance for integrating and consolidating memories.

A Weak Connection

Our proposal that the brain uses neuronal firing during sleep to weaken rather than strengthen synapses is supported in part by close analyses of data from a standard workhorse of sleep research: the electroencephalogram, or EEG. EEGs record patterns of electrical activity in the cerebral cortex via electrodes attached to the scalp. Decades ago EEG recordings of the sleeping brain revealed two main categories of sleep, called rapid eye movement (REM) and non-REM (NREM), that alternate throughout the night. Each has distinctive brain-wave patterns. In addition to the jittering of eyeballs underneath closed lids that gives REM sleep its name, that stage is dominated by relatively fast oscillations—quick ups and downs in the curves of the EEG readout, resembling EEG recordings of the waking state. In contrast, slow oscillations—with frequencies of about one cycle per second—are the most prominent feature of NREM sleep.

A decade ago the late Mircea Steriade of Laval University in Quebec discovered that the slow oscillations of NREM sleep arise when groups of neurons fire together for a little while (so-called on periods), then fall silent for about a fraction of a second (off periods) and then resume their synchronized firing. This was one of the fundamental discoveries in sleep research. Since then, scientists have also discovered that in birds and mammals, the slow waves are large if preceded by a long period of wakefulness and become smaller as sleep goes on.

We reasoned that if synapses are strong, neurons will synchronize their firing more, producing larger slow waves. If synapses are weak, neurons will be less synchronized and the resulting slow waves will be smaller. Results of computer simulations and experiments in humans and animals led us to conclude that the big, steep slow waves early in the night indicate that synapses have been strengthened by prior wakefulness, whereas the small, shallow slow waves early in the morning indicate that synapses have become weaker during sleep.

Direct support for the idea that synapses become weaker during sleep, and may even be pruned away, comes from studies in animals. In fruit flies, for instance, we find that sleep reverses a progressive increase in the number and size of synapses that occurs during the day, especially when the flies are exposed to stimulating environments. Synaptic spines are specialized protrusions on a neuron's signal-detecting arm. When fruit flies spend the day interacting with other flies, neurons throughout their brain sprout more synaptic spines by evening than were present in the morning.

Just as remarkably, the number of spines goes back to the baseline level by the following morning if—and only if—the flies are allowed to sleep. We saw a similar phenomenon in the cerebral cortex of adolescent mice: the number of synaptic spines tended to rise when the animals were awake and to fall when they slept. In adult rodents, the upshot is the same, although it is not the number of synaptic spines that changes with wakefulness and sleep but rather the abundance of certain spine molecules, known as AMPA receptors, that determine the strength of a synapse. When we monitored these AMPA receptors, we found that their number per synapse increases after wakefulness and decreases after sleep. More receptors make for stronger synapses; fewer mean the synapses have weakened.

Synaptic strength can be gauged directly by using an electrical probe to stimulate neural fibers in the cortex. The neurons respond with an induced electrical discharge that is larger when synapses are strong and smaller when the connections are weak. We showed that in rats, stimulated neurons fire more strongly after a few hours of wakefulness and less strongly after sleep. Marcello Massimini of the University of Milan in Italy and Reto Huber, now at the University of Zurich, performed a similar experiment in humans. Instead of an electrical probe, they turned to transcranial magnetic stimulation—a short magnetic pulse applied to the scalp—to stimulate the underlying neurons. They then recorded the strength of the cortical responses with high-density EEG. The results were clear: the longer a subject was awake, the larger the EEG responses. It took a night of sleep for cortical responses to return to the baseline.

Less Is More

The common conclusion of these experiments, which we performed over two decades, is that spontaneous cortical activity in sleep does indeed weaken the synaptic connections in neural circuits, whether by damping their ability to send electrical impulses or by erasing them outright.

This process, which we call down selection, would ensure the survival of the circuits that are “fittest,” either because they were activated strongly and consistently during wakefulness (say, by playing the right notes on a guitar while trying to master a new piece) or because they were better integrated with previous, older memories (as would be the case for a new word encountered in a known language). Meanwhile synapses in circuits that were only mildly enhanced during wakefulness (such as fumbled notes on the guitar) or that fit less with old memories (such as a new word presented in an unknown language) would be depressed.

Down selection would ensure that insignificant events would leave no lasting trace in our neural circuitry, whereas memories of note would be preserved. As an additional bonus, down selection would also make room for another cycle of synaptic strengthening during wakefulness. Indeed, some findings imply that among its many other benefits for learning and memory, sleep aids the subsequent acquisition of new memories (material encountered before the next bout of sleep). Quite a few studies have shown that after a night of sleep, you can learn new material much better than you can after having been awake all day. (Students, take note.)

Although we have no direct evidence for a mechanism that would produce selective weakening of activated synapses as yet, we have a notion of how synaptic weakening could occur. We suspect the slow waves of mammalian NREM sleep somehow play a role. In lab studies of rat brain tissue, nerve cells became less effective at passing signals to one another when stimulated in ways that mimic the synchronized on/off cycles of slow-wave sleep.

The chemistry of the brain also changes in NREM sleep in a way that could lead to synaptic weakening. In the awake individual, a concentrated soup of signaling chemicals, or neuromodulators—including acetylcholine, norepinephrine, dopamine, serotonin, histamine and hypocretin—bathe the brain and bias synapses toward strengthening when signals pass through them. During sleep—especially NREM sleep—the soup becomes much less concentrated. This diluted milieu of neuromodulators may bias the neural circuitry so that synapses become weakened, rather than strengthened, when signals flow across them. The process might also involve a substance called brain-derived neurotrophic factor (BDNF), which is known to promote synaptic strengthening and to be involved in memory acquisition. BDNF levels are high in neurons during wakefulness and minimal during sleep.

Local Sleep

Regardless of specific mechanisms and selective processes, the evidence is strong in several species that overall synaptic strength goes up during wakefulness and down during sleep: the core prediction of SHY. We can test SHY further by examining some of its intriguing corollaries.

For example, if the hypothesis is correct, then the more plasticity a part of the brain undergoes during wakefulness, the more that part should need to sleep. “Sleep need” can, in turn, be indicated by an increase in the size and duration of NREM slow waves. To explore this prediction, we asked human subjects to learn a novel task: how to reach a target on a computer screen while the cursor (controlled by a mouse) is systematically rotated. The part of the brain that engages in this kind of learning is the right parietal cortex. Sure enough, when our subjects slept, the slow waves over their right parietal cortex were larger, relative to waves from the same area on the night before learning occurred. These large waves did flatten out in the course of the night, as such oscillations do. But those large, localized waves at the start of the night tell us that particular part of the brain had been exhausted by the task we assigned.

Many other experiments by the two of us and others have since confirmed that learning, and more generally the activation of synapses in circuits, produces a local increase in sleep need. Recently we have even found that prolonged or intense use of certain circuits can make local groups of neurons “fall asleep” even though the rest of the brain (and the organism itself) remains awake. Thus, if a rat stays awake longer than usual, some cortical neurons show brief periods of silence that are basically indistinguishable from the off periods observed during slow-wave sleep. Meanwhile the rat is running around, its eyes open, tending to its business, as any awake rat would do.

This phenomenon is called local sleep, and it is attracting scrutiny from other investigators. Our latest studies indicate that localized off periods also occur in the brains of sleep-deprived humans and that those periods become more frequent after intense learning. It seems that when we have been awake for too long or have overexerted certain circuits, small chunks of the brain may take quick naps without giving notice. One wonders how many errors of judgment, silly mistakes, irritable responses and foul moods result from local sleep in the brains of exhausted people who believe they are fully awake and in complete control.

SHY also predicts that sleep is especially important in childhood and adolescence, times of concentrated learning and of intense synaptic remodeling, as many studies have shown. In youth, synapses are formed, strengthened and pruned at an explosive rate never approached in adulthood. It makes sense that down selection during sleep would be crucial to minimize the energy costs of this frenzied synaptic remodeling and to favor the survival of adaptive neural circuits in these stages of life. One can only wonder what happens when sleep is disrupted or insufficient during critical periods in development. Might the deficit corrupt the proper refinement of neural circuits? In that case, the effect of sleep loss would not merely be occasional forgetfulness or misjudgment but a lasting change in the way the brain is wired.

We look forward to testing SHY's predictions and exploring its implications further. For example, we hope to discover whether sleep deprivation during neural development leads to changes in the organization of brain circuitry. We would also like to learn more about the effect of sleep on deep-brain areas, such as the thalamus, cerebellum, hypothalamus and brain stem, and about the role of REM sleep in synaptic homeostasis. Perhaps we would then learn if sleep is indeed the price of waking plasticity, a price that every brain and every neuron must pay.

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Restorative Theory and More Ideas About Why We Sleep

Restorative theory, adaptive theory.

• Energy Conservation
• Brain Plasticity

Frequently Asked Questions

Even though it's something you have to do every day, why we sleep remains a mystery. Many sleep theories abound, yet scientists are far from universal agreement about how to answer the question, "Why do we sleep at night?" Only in the last few decades have they even begun to unravel sleep's true secrets. At least four common theories are in play, but it remains to be seen which—if any—are correct.

You may look at these theories and the scientific evidence that supports them and wonder why they all can't, at least in part, be right. They could be, but researchers are continuing to search for "the" core reason for sleep, and many subscribe to a belief expressed in a 1998 paper:  

Allen Rechtschaffen

Sleep can be understood as fulfilling many different functions but intuition suggests there is one essential function. The discovery of this function will open an important door to the understanding of biological processes.

The sleep cycle involves several stages, but these theories generally focus on rapid-eye movement (REM) sleep —which is when you dream —and the other stages lumped together as non-REM sleep.

The restorative theory of sleep, first proposed in 2006, is among the more accepted explanations for why people need sleep. It suggests that the purpose of sleep is to store memory and restore our brains and bodies for the next day.

• Organizing and storing memories : Memories are believed to be converted from short-term to long-term storage, while information deemed unimportant is removed. This primarily occurs during REM sleep, which is when the brain cells most involved in memory, attention, and learning are least active.
• Clearing out and replenishing brain chemicals : Many brain chemicals build up while you're awake, including adenosine , which makes you sleepy when it accumulates. Meanwhile, during sleep, the brain "restocks" the chemicals it uses for sending signals and other purposes, so you have enough for the next day.
• Clearing waste toxins from the brain : Similar to brain chemicals, the waste products of energy metabolism build up during the day and are cleared out at night. (However, the primary evidence for this comes from studies of mice, not humans.)
• Repairing tissues throughout the body : During sleep, your body increases cellular division, growth hormone levels, and the production of proteins necessary for proper function. This is believed to be why strenuous physical activity during the day increases your time in REM sleep.
• Rest for the brain : The inactivity during non-REM sleep appears to provide a period of rest for the brain.

Some of the brain chemicals that accumulate during the day are associated with the plaques that characterize Alzheimer's disease , so it's theorized that the brain-clearing activities of sleep may protect you against Alzheimer's.

Also called the evolution theory or preservation theory, the original version of this early theory suggested that while humans evolved, hiding out overnight increased the ability to survive.  

For our early ancestors, nighttime was dangerous—especially because the predators who hunt at night function better in the dark than humans do—so it made sense to seek a safe refuge. Also, because they couldn't be out finding food themselves, their bodies slowed down to conserve energy for when they could be active. People who avoided dangers in this way, the theory argued, lived longer and were more likely to reproduce.

Thus, sleep became an adaptive or evolutionary advantage and became part of the neurochemistry of the species. However, most experts reject this idea because sleeping leaves animals (including humans) vulnerable and defenseless, which doesn't support the idea that sleeping made our ancestors safer.

A flaw in this theory, some experts say, is that sleeping limits productivity, such as finding food and reproducing, so staying awake longer would be an evolutionary benefit.   However, no species evolved without a need for sleep, which calls the adaptive benefit into question.

According to some sleep researchers, the daily need for sleep combined with the incentive not to be out in the dark caused us to adapt to function best during daylight, which prevented us from adapting to the dark.  

Energy Conservation Theory

In a similar vein to aspects of other theories, some experts theorize the primary purpose of sleep is conserving energy. By sleeping, they say, you're able to spend part of your time functioning at a lower metabolism.

That lowers the number of calories you need to eat. For early humans, that extra food requirement could have been the difference between life and death, or survival of the species versus extinction. It was harder to gather food at night, so it made sense to stay hidden then. They also point to the brain's need to replenish its reserve of glycogen, which is an important fuel.

However, while it's true that metabolism slows during non-REM, the brain is extremely active during REM sleep, which some say is a strike against the energy conservation theory.

Brain Plasticity Theory

Among the more recent theories deals with brain plasticity (also called neuroplasticity), which is the brain's ability to change and adapt in response to experience. It can change both functional aspects (such as re-learning skills in a new area after damage) and structural aspects (such as forming new pathways due to learning).

The brain plasticity theory says that sleep is necessary for the brain to make structural changes. Support for this theory comes from many places.

As in restorative theory, this concept deals with information processing and memory formation. Research suggests that sleep loss leads to less structural plasticity, which can have a negative effect on alertness, cognition, and mood. Sleep deprivation also compromises memory formation, which is related to learning and plasticity.  

It's believed that the plasticity theory explains why babies and young children require a lot of sleep—they're learning so much about the world that their brains need more time to process it. Researchers are even trying to promote less sleep interruption for preterm babies in neonatal intensive care, citing studies about sleep's long-term impact on brain development and plasticity.  

Some researchers have even theorized that sleep is the price we pay for brain plasticity. That concept is based on the importance of the processes that occur during sleep to the brain's ability to adapt and change.  

Declining Sleep Needs

Newborns need between 14 and 17 hours of sleep per day. The recommended amount of sleep declines throughout childhood, with teenagers needing between 8 and 10 hours a day.

Why do we close our eyes when we sleep?

There are several reasons why most people sleep with eyes closed, though some people do actually sleep with their eyes open. Closed eyes stay moist and are protected by the eyelids during sleep. Eyelids also block out light during sleep, and light signals to the brain that it is time to wake up.

At what stage of sleep can you experience sleep paralysis?

Sleep paralysis , or the feeling that you are conscious and yet unable to control your body, is very common and typically occurs during the transition from REM to being awake.

Why do we dream?

There are a lot of theories explaining why we dream, such as that dreaming aids in memory processing and that it allows us to process emotions. Sigmund Freud believed that dreams express our unconscious desires and deepest wishes.

A Word From Verywell

While it's a phenomenon we don't fully understand, sleep is critical to our daily health. Not only is it necessary for restoration and repair, learning and memory, growth and development, and brain plasticity, sleep also helps with problem-solving, a healthy metabolism, blood-sugar and hormone regulation, heart health, and strengthening immunity.   With how crucial it is to our survival, it's no wonder many of us long for more of it.

Freiberg AS. Why we sleep: A hypothesis for an ultimate or evolutionary origin for sleep and other physiological rhythms .  J Circadian Rhythms . 2020;18:2. Published 2020 Mar 30. doi:10.5334/jcr.189

Ezenwanne E. Current concepts in the neurophysiologic basis of sleep; a review .  Ann Med Health Sci Res ; 1(2):173-179.

Xie L, Kang H, Xu Q, et al.  Sleep drives metabolite clearance from the adult brain .  Science . 2013;342(6156):373–377. doi:10.1126/science.1241224

Raven F, Van der Zee EA, Meerlo P, Havekes R. The role of sleep in regulating structural plasticity and synaptic strength: Implications for memory and cognitive function .  Sleep Med Rev . 2018;39:3-11. doi:10.1016/j.smrv.2017.05.002

Park J. Sleep promotion for preterm infants in the NICU .  Nurs Womens Health . 2020;24(1):24-35. doi:10.1016/j.nwh.2019.11.004

Tononi G, Cirelli C. Sleep and the price of plasticity: From synaptic and cellular homeostasis to memory consolidation and integration .  Neuron . 2014;81(1):12-34. doi:10.1016/j.neuron.2013.12.025

U.S. Centers for Disease Control and Prevention. Sleep and sleep disorders: How much sleep do I need?

National Sleep Foundation. Can you really sleep with your eyes open ?

Rasch B, Born J.  About sleep's role in memory .  Physiol Rev . 2013;93(2):681-766. doi:10.1152/physrev.00032.2012

Zhang W, Guo B.  Freud's dream interpretation: A different perspective based on the self-organization theory of dreaming .  Front Psychol . 2018;9:1553. doi:10.3389/fpsyg.2018.01553

National Institutes of Health, National Heart, Lung, and Blood Institute. Sleep deprivation and deficiency .

By Brandon Peters, MD Dr. Peters is a board-certified neurologist and sleep medicine specialist and is a fellow of the American Academy of Sleep Medicine.

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Why We Sleep: A Hypothesis for an Ultimate or Evolutionary Origin for Sleep and Other Physiological Rhythms

Affiliation.

• 1 Penn State Health, Department of Pediatrics, Penn State Hershey Medical Center, Hershey, PA, US.
• PMID: 32269596
• PMCID: PMC7120898
• DOI: 10.5334/jcr.189

Although sleep is ubiquitous, its evolutionary purpose remains elusive. Though every species of animal, as well as many plants sleep, theories of its origin are purely physiological, e.g. to conserve energy, make repairs or to consolidate learning. An evolutionary reason for sleep would answer one of biology's fundamental unanswered questions. When environmental conditions change on a periodic basis (winter/summer, day/night) organisms must somehow confront the change or else be less able to compete in either niche. Seasonal adaptation includes the migration of birds, changes in honeybee physiology and winter abscission in plants. Diurnal adaptation must be more rapid, forcing changes in behavior in addition to physiology. Since organisms must exist in both environments, evolution has created a way to force a change in behavior, in effect creating "different" organisms (one awake, one asleep) adapted separately to two distinct niches. We sleep to allow evolving into two competing niches. The physiology of sleep forces a change to a different state for the second niche. The physiological needs for sleep are mechanisms that have evolved to achieve this goal.

Keywords: adaptive theory; evolution; physiology; proximate cause; restorative theory; sleep; ultimate cause.

Copyright: © 2020 The Author(s).

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Conflict of interest statement

The author has no competing interests to declare.

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4.2 Sleep and Why We Sleep

Learning objectives.

By the end of this section, you will be able to:

• Describe areas of the brain involved in sleep
• Understand hormone secretions associated with sleep
• Describe several theories aimed at explaining the function of sleep
• Name and describe three theories about why we dream

We spend approximately one-third of our lives sleeping. Given the average life expectancy for U.S. citizens falls between 73 and 79 years old (Singh & Siahpush, 2006), we can expect to spend approximately 25 years of our lives sleeping. Some animals never sleep (e.g., some fish and amphibian species); other animals sleep very little without apparent negative consequences (e.g., giraffes); yet some animals (e.g., rats) die after two weeks of sleep deprivation (Siegel, 2008). Why do we devote so much time to sleeping? Is it absolutely essential that we sleep? This section will consider these questions and explore various explanations for why we sleep.

What is Sleep?

You have read that sleep is distinguished by low levels of physical activity and reduced sensory awareness. As discussed by Siegel (2008), a definition of sleep must also include mention of the interplay of the circadian and homeostatic mechanisms that regulate sleep. Homeostatic regulation of sleep is evidenced by sleep rebound following sleep deprivation. Sleep rebound refers to the fact that a sleep-deprived individual will fall asleep more quickly during subsequent opportunities for sleep. Sleep is characterized by certain patterns of activity of the brain that can be visualized using electroencephalography (EEG), and different phases of sleep can be differentiated using EEG as well.

Sleep-wake cycles seem to be controlled by multiple brain areas acting in conjunction with one another. Some of these areas include the thalamus, the hypothalamus, and the pons. As already mentioned, the hypothalamus contains the SCN—the biological clock of the body—in addition to other nuclei that, in conjunction with the thalamus, regulate slow-wave sleep. The pons is important for regulating rapid eye movement (REM) sleep (National Institutes of Health, n.d.).

Sleep is also associated with the secretion and regulation of a number of hormones from several endocrine glands including: melatonin, follicle stimulating hormone (FSH), luteinizing hormone (LH), and growth hormone (National Institutes of Health, n.d.). You have read that the pineal gland releases melatonin during sleep ( Figure 4.6 ). Melatonin is thought to be involved in the regulation of various biological rhythms and the immune system (Hardeland et al., 2006). During sleep, the pituitary gland secretes both FSH and LH which are important in regulating the reproductive system (Christensen et al., 2012; Sofikitis et al., 2008). The pituitary gland also secretes growth hormone, during sleep, which plays a role in physical growth and maturation as well as other metabolic processes (Bartke, Sun, & Longo, 2013).

Why Do We Sleep?

Given the central role that sleep plays in our lives and the number of adverse consequences that have been associated with sleep deprivation, one would think that we would have a clear understanding of why it is that we sleep. Unfortunately, this is not the case; however, several hypotheses have been proposed to explain the function of sleep.

Adaptive Function of Sleep

One popular hypothesis of sleep incorporates the perspective of evolutionary psychology. Evolutionary psychology is a discipline that studies how universal patterns of behavior and cognitive processes have evolved over time as a result of natural selection . Variations and adaptations in cognition and behavior make individuals more or less successful in reproducing and passing their genes to their offspring. One hypothesis from this perspective might argue that sleep is essential to restore resources that are expended during the day. Just as bears hibernate in the winter when resources are scarce, perhaps people sleep at night to reduce their energy expenditures. While this is an intuitive explanation of sleep, there is little research that supports this explanation. In fact, it has been suggested that there is no reason to think that energetic demands could not be addressed with periods of rest and inactivity (Frank, 2006; Rial et al., 2007), and some research has actually found a negative correlation between energetic demands and the amount of time spent sleeping (Capellini, Barton, McNamara, Preston, & Nunn, 2008).

Another evolutionary hypothesis of sleep holds that our sleep patterns evolved as an adaptive response to predatory risks, which increase in darkness. Thus we sleep in safe areas to reduce the chance of harm. Again, this is an intuitive and appealing explanation for why we sleep. Perhaps our ancestors spent extended periods of time asleep to reduce attention to themselves from potential predators. Comparative research indicates, however, that the relationship that exists between predatory risk and sleep is very complex and equivocal. Some research suggests that species that face higher predatory risks sleep fewer hours than other species (Capellini et al., 2008), while other researchers suggest there is no relationship between the amount of time a given species spends in deep sleep and its predation risk (Lesku, Roth, Amlaner, & Lima, 2006).

It is quite possible that sleep serves no single universally adaptive function, and different species have evolved different patterns of sleep in response to their unique evolutionary pressures. While we have discussed the negative outcomes associated with sleep deprivation, it should be pointed out that there are many benefits that are associated with adequate amounts of sleep. A few such benefits listed by the National Sleep Foundation (n.d.) include maintaining health, lowering stress levels, improving mood, and increasing motor coordination, as well as a number of benefits related to cognition and memory formation.

Cognitive Function of Sleep

Another theory regarding why we sleep involves sleep’s importance for cognitive function and memory formation (Rattenborg, Lesku, Martinez-Gonzalez, & Lima, 2007). Indeed, we know sleep deprivation results in disruptions in cognition and memory deficits (Brown, 2012), leading to impairments in our abilities to maintain attention, make decisions, and recall long-term memories. Moreover, these impairments become more severe as the amount of sleep deprivation increases (Alhola & Polo-Kantola, 2007). Furthermore, slow-wave sleep after learning a new task can improve resultant performance on that task (Huber, Ghilardi, Massimini, & Tononi, 2004) and seems essential for effective memory formation (Stickgold, 2005). Understanding the impact of sleep on cognitive function should help you understand that cramming all night for a test may not be effective and can even prove counterproductive.

Link to Learning

Watch this brief video that gives sleep tips for college students to learn more.

Getting the optimal amount of sleep has also been associated with other cognitive benefits. Research indicates that included among these possible benefits are increased capacities for creative thinking (Cai, Mednick, Harrison, Kanady, & Mednick, 2009; Wagner, Gais, Haider, Verleger, & Born, 2004), language learning (Fenn, Nusbaum, & Margoliash, 2003; Gómez, Bootzin, & Nadel, 2006), and inferential judgments (Ellenbogen, Hu, Payne, Titone, & Walker, 2007). It is possible that even the processing of emotional information is influenced by certain aspects of sleep (Walker, 2009).

Watch this brief video about the relationship between sleep and memory to learn more.

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• Published: 20 December 2018

Exploring phylogeny to find the function of sleep

• Ron C. Anafi 1 , 2 ,
• Matthew S. Kayser 2 , 3 &
• David M. Raizen 1 , 2 , 4  

Nature Reviews Neuroscience volume  20 ,  pages 109–116 ( 2019 ) Cite this article

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• Non-REM sleep
• Sleep deprivation

During sleep, animals do not eat, reproduce or forage. Sleeping animals are vulnerable to predation. Yet, the persistence of sleep despite evolutionary pressures, and the deleterious effects of sleep deprivation, indicate that sleep serves a function or functions that cannot easily be bypassed. Recent research demonstrates sleep to be phylogenetically far more pervasive than previously appreciated; it is possible that the very first animals slept. Here, we give an overview of sleep across various species, with the aim of determining its original purpose. Sleep exists in animals without cephalized nervous systems and can be influenced by non-neuronal signals, including those associated with metabolic rhythms. Together, these observations support the notion that sleep serves metabolic functions in neural and non-neural tissues.

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Acknowledgements

The authors thank A. Rohacek and S. Belfer for comments. R.C.A. is supported by US Defense Advanced Research Projects Agency grant D17AP00003; M.S.K. is supported by K08NS090461 (US National Institutes of Health), a Burroughs Wellcome Career Award for Medical Scientists, a March of Dimes Basil O’Connor Scholar Award and a Sloan Research Fellowship; and D.M.R. is supported by R01NS088432 (US National Institutes of Health).

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Anafi, R.C., Kayser, M.S. & Raizen, D.M. Exploring phylogeny to find the function of sleep. Nat Rev Neurosci 20 , 109–116 (2019). https://doi.org/10.1038/s41583-018-0098-9

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4.2 Sleep & Why We Sleep

Learning objectives.

By the end of this section, you will be able to:

• Describe areas of the brain involved in sleep
• Understand hormone secretions associated with sleep
• Describe several theories aimed at explaining the function of sleep

   We spend approximately one-third of our lives sleeping. Given the average life expectancy for U.S. citizens falls between 73 and 79 years old (Singh & Siahpush, 2006), we can expect to spend approximately 25 years of our lives sleeping. Some animals never sleep (e.g., several fish and amphibian species); other animals can go extended periods of time without sleep and without apparent negative consequences (e.g., dolphins); yet some animals (e.g., rats) die after two weeks of sleep deprivation (Siegel, 2008). Why do we devote so much time to sleeping? Is it absolutely essential that we sleep? This section will consider these questions and explore various explanations for why we sleep.

WHAT IS SLEEP?

   You have read that sleep is distinguished by low levels of physical activity and reduced sensory awareness. As discussed by Siegel (2008), a definition of sleep must also include mention of the interplay of the circadian and homeostatic mechanisms that regulate sleep. Homeostatic regulation of sleep is evidenced by sleep rebound following sleep deprivation. Sleep rebound refers to the fact that a sleep-deprived individual will tend to take a shorter time to fall asleep during subsequent opportunities for sleep. Sleep is characterized by certain patterns of activity of the brain that can be visualized using electroencephalography (EEG), and different phases of sleep can be differentiated using EEG as well (figure below).

This is a segment of a polysonograph (PSG), a recording of several physical variables during sleep. The x -axis shows passage of time in seconds; this record includes 30 seconds of data. The location of the sets of electrode that produced each signal is labeled on the y -axis. The red box encompasses EEG output, and the waveforms are characteristic of a specific stage of sleep. Other curves show other sleep-related data, such as body temperature, muscle activity, and heartbeat.

   Sleep-wake cycles seem to be controlled by multiple brain areas acting in conjunction with one another. Some of these areas include the thalamus, the hypothalamus, and the pons. As already mentioned, the hypothalamus contains the SCN—the biological clock of the body—in addition to other nuclei that, in conjunction with the thalamus, regulate slow-wave sleep. The pons is important for regulating rapid eye movement (REM) sleep (National Institutes of Health, n.d.).

Sleep is also associated with the secretion and regulation of a number of hormones from several endocrine glands including: melatonin, follicle stimulating hormone (FSH), luteinizing hormone (LH), and growth hormone (National Institutes of Health, n.d.). You have read that the pineal gland releases melatonin during sleep (figure below). Melatonin is thought to be involved in the regulation of various biological rhythms and the immune system (Hardeland et al., 2006). During sleep, the pituitary gland secretes both FSH and LH which are important in regulating the reproductive system (Christensen et al., 2012; Sofikitis et al., 2008). The pituitary gland also secretes growth hormone, during sleep, which plays a role in physical growth and maturation as well as other metabolic processes (Bartke, Sun, & Longo, 2013).

Although it is still unclear exactly which hormones cause one to sleep, new studies have shown that melanin-concentrating hormone (MCH) neurons promote sleep in the brain. They discharge action potentials during both NREM and REM sleep to regulate these sleep states. Recent studies have also shown that sex hormones may have an effect on sleep-wake cycles. One study found that males may be more prone to sleep apnea due to their lower levels of progesterone (Empson & Purdie, 1999). Yet another theory for why we sleep is that it is important for information consolidation (i.e., solidifying information in long-term memory). One study examined this theory by dividing 28 participants into two groups and having them learn 12 new words at either 10:00 am or 10:00 pm. They hypothesized that the participants learning the words at 10:00 pm would have better recollection based on the assumption that they were closer to going to sleep (and therefore closer to entering a state in which they could consolidate the new information). This is not, however, what they found. They found that there was no significant difference in the recollection of words based on the time those words were learned (Bengino, 2006).

The pineal and pituitary glands secrete a number of hormones during sleep.

Why do we sleep.

   Given the central role that sleep plays in our lives and the number of adverse consequences that have been associated with sleep deprivation, one would think that we would have a clear understanding of why it is that we sleep. Unfortunately, this is not the case; however, several hypotheses have been proposed to explain the function of sleep.

Adaptive Function of Sleep

One popular hypothesis of sleep incorporates the perspective of evolutionary psychology. Evolutionary psychology is a discipline that studies how universal patterns of behavior and cognitive processes have evolved over time as a result of natural selection . Variations and adaptations in cognition and behavior make individuals more or less successful in reproducing and passing their genes to their offspring. One hypothesis from this perspective might argue that sleep is essential to restore resources that are expended during the day. Just as bears hibernate in the winter when resources are scarce, perhaps people sleep at night to reduce their energy expenditures. While this is an intuitive explanation of sleep, there is little research that supports this explanation. In fact, it has been suggested that there is no reason to think that energetic demands could not be addressed with periods of rest and inactivity (Frank, 2006; Rial et al., 2007), and some research has actually found a negative correlation between energetic demands and the amount of time spent sleeping (Capellini, Barton, McNamara, Preston, & Nunn, 2008).

Another evolutionary hypothesis of sleep holds that our sleep patterns evolved as an adaptive response to predatory risks, which increase in darkness. Thus we sleep in safe areas to reduce the chance of harm. Again, this is an intuitive and appealing explanation for why we sleep. Perhaps our ancestors spent extended periods of time asleep to reduce attention to themselves from potential predators. Comparative research indicates, however, that the relationship that exists between predatory risk and sleep is very complex and equivocal. Some research suggests that species that face higher predatory risks sleep fewer hours than other species (Capellini et al., 2008), while other researchers suggest there is no relationship between the amount of time a given species spends in deep sleep and its predation risk (Lesku, Roth, Amlaner, & Lima, 2006).

It is quite possible that sleep serves no single universally adaptive function, and different species have evolved different patterns of sleep in response to their unique evolutionary pressures. While we have discussed the negative outcomes associated with sleep deprivation, it should be pointed out that there are many benefits that are associated with adequate amounts of sleep. A few such benefits listed by the National Sleep Foundation (n.d.) include maintaining healthy weight, lowering stress levels, improving mood, and increasing motor coordination, as well as a number of benefits related to cognition and memory formation.

Cognitive Function of Sleep

   Another theory regarding why we sleep involves sleep’s importance for cognitive function and memory formation (Rattenborg, Lesku, Martinez-Gonzalez, & Lima, 2007). Indeed, we know sleep deprivation results in disruptions in cognition and memory deficits (Brown, 2012), leading to impairments in our abilities to maintain attention, make decisions, and recall long-term memories. Moreover, these impairments become more severe as the amount of sleep deprivation increases (Alhola & Polo-Kantola, 2007). Furthermore, slow-wave sleep after learning a new task can improve resultant performance on that task (Huber, Ghilardi, Massimini, & Tononi, 2004) and seems essential for effective memory formation (Stickgold, 2005). Understanding the impact of sleep on cognitive function should help you understand that cramming all night for a test may be not effective and can even prove counterproductive.

   Sleep has also been associated with other cognitive benefits. Research indicates that included among these possible benefits are increased capacities for creative thinking (Cai, Mednick, Harrison, Kanady, & Mednick, 2009; Wagner, Gais, Haider, Verleger, & Born, 2004), language learning (Fenn, Nusbaum, & Margoliash, 2003; Gómez, Bootzin, & Nadel, 2006), and inferential judgments (Ellenbogen, Hu, Payne, Titone, & Walker, 2007). It is possible that even the processing of emotional information is influenced by certain aspects of sleep (Walker, 2009).

   We devote a very large portion of time to sleep, and our brains have complex systems that control various aspects of sleep. Several hormones important for physical growth and maturation are secreted during sleep. While the reason we sleep remains something of a mystery, there is some evidence to suggest that sleep is very important to learning and memory.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions: 

1. Growth hormone is secreted by the ________ while we sleep.

a. pineal gland

c. pituitary gland

d. pancreas

2. The ________ plays a role in controlling slow-wave sleep.

a. hypothalamus

b. thalamus

d. both a and b

3. ________ is a hormone secreted by the pineal gland that plays a role in regulating biological rhythms and immune function.

a. growth hormone

b. melatonin

4. ________ appears to be especially important for enhanced performance on recently learned tasks.

a. melatonin

b. slow-wave sleep

c. sleep deprivation

d. growth hormone

5. What does the acronym ‘REM’ stand for?

a. Restless Eye Movement

b. Rapid Evolutionary Moments

c. Rapid Eye Movement

d. Recurring Evolutionary Minds

6. What is ‘manifest content’?

a. Being able to recall the events in your dreams

b. The hidden meaning of a dream

c. The act of dreaming while in deep sleep

d. The actual content of a dream

Critical Thinking Questions:

1. If theories that assert sleep is necessary for restoration and recovery from daily energetic demands are correct, what do you predict about the relationship that would exist between individuals’ total sleep duration and their level of activity?

2. How could researchers determine if given areas of the brain are involved in the regulation of sleep?

3. Differentiate the evolutionary theories of sleep and make a case for the one with the most compelling evidence.

Personal Application Question:

1. Have you (or someone you know) ever experienced significant periods of sleep deprivation because of simple insomnia, high levels of stress, or as a side effect from a medication? What were the consequences of missing out on sleep?

evolutionary psychology

sleep rebound 

Answers to Exercises

1.  Those individuals (or species) that expend the greatest amounts of energy would require the longest periods of sleep.

2.  Researchers could use lesion or brain stimulation techniques to determine how deactivation or activation of a given brain region affects behavior. Furthermore, researchers could use any number of brain imaging techniques like fMRI or CT scans to come to these conclusions.

3.  One evolutionary theory of sleep holds that sleep is essential for restoration of resources that are expended during the demands of day-to-day life. A second theory proposes that our sleep patterns evolved as an adaptive response to predatory risks, which increase in darkness. The first theory has little or no empirical support, and the second theory is supported by some, though not all, research.

evolutionary psychology:  discipline that studies how universal patterns of behavior and cognitive processes have evolved over time as a result of natural selection

sleep rebound:  sleep-deprived individuals will experience shorter sleep latencies during subsequent opportunities for sleep

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when  conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a  correlational study  can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

15 Hypothesis Examples

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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A hypothesis is defined as a testable prediction , and is used primarily in scientific experiments as a potential or predicted outcome that scientists attempt to prove or disprove (Atkinson et al., 2021; Tan, 2022).

In my types of hypothesis article, I outlined 13 different hypotheses, including the directional hypothesis (which makes a prediction about an effect of a treatment will be positive or negative) and the associative hypothesis (which makes a prediction about the association between two variables).

This article will dive into some interesting examples of hypotheses and examine potential ways you might test each one.

Hypothesis Examples

1. “inadequate sleep decreases memory retention”.

Field: Psychology

Type: Causal Hypothesis A causal hypothesis explores the effect of one variable on another. This example posits that a lack of adequate sleep causes decreased memory retention. In other words, if you are not getting enough sleep, your ability to remember and recall information may suffer.

How to Test:

To test this hypothesis, you might devise an experiment whereby your participants are divided into two groups: one receives an average of 8 hours of sleep per night for a week, while the other gets less than the recommended sleep amount.

During this time, all participants would daily study and recall new, specific information. You’d then measure memory retention of this information for both groups using standard memory tests and compare the results.

Should the group with less sleep have statistically significant poorer memory scores, the hypothesis would be supported.

Ensuring the integrity of the experiment requires taking into account factors such as individual health differences, stress levels, and daily nutrition.

Relevant Study: Sleep loss, learning capacity and academic performance (Curcio, Ferrara & De Gennaro, 2006)

2. “Increase in Temperature Leads to Increase in Kinetic Energy”

Field: Physics

Type: Deductive Hypothesis The deductive hypothesis applies the logic of deductive reasoning – it moves from a general premise to a more specific conclusion. This specific hypothesis assumes that as temperature increases, the kinetic energy of particles also increases – that is, when you heat something up, its particles move around more rapidly.

This hypothesis could be examined by heating a gas in a controlled environment and capturing the movement of its particles as a function of temperature.

You’d gradually increase the temperature and measure the kinetic energy of the gas particles with each increment. If the kinetic energy consistently rises with the temperature, your hypothesis gets supporting evidence.

Variables such as pressure and volume of the gas would need to be held constant to ensure validity of results.

3. “Children Raised in Bilingual Homes Develop Better Cognitive Skills”

Field: Psychology/Linguistics

Type: Comparative Hypothesis The comparative hypothesis posits a difference between two or more groups based on certain variables. In this context, you might propose that children raised in bilingual homes have superior cognitive skills compared to those raised in monolingual homes.

Testing this hypothesis could involve identifying two groups of children: those raised in bilingual homes, and those raised in monolingual homes.

Cognitive skills in both groups would be evaluated using a standard cognitive ability test at different stages of development. The examination would be repeated over a significant time period for consistency.

If the group raised in bilingual homes persistently scores higher than the other, the hypothesis would thereby be supported.

The challenge for the researcher would be controlling for other variables that could impact cognitive development, such as socio-economic status, education level of parents, and parenting styles.

Relevant Study: The cognitive benefits of being bilingual (Marian & Shook, 2012)

4. “High-Fiber Diet Leads to Lower Incidences of Cardiovascular Diseases”

Field: Medicine/Nutrition

Type: Alternative Hypothesis The alternative hypothesis suggests an alternative to a null hypothesis. In this context, the implied null hypothesis could be that diet has no effect on cardiovascular health, which the alternative hypothesis contradicts by suggesting that a high-fiber diet leads to fewer instances of cardiovascular diseases.

To test this hypothesis, a longitudinal study could be conducted on two groups of participants; one adheres to a high-fiber diet, while the other follows a diet low in fiber.

After a fixed period, the cardiovascular health of participants in both groups could be analyzed and compared. If the group following a high-fiber diet has a lower number of recorded cases of cardiovascular diseases, it would provide evidence supporting the hypothesis.

Control measures should be implemented to exclude the influence of other lifestyle and genetic factors that contribute to cardiovascular health.

Relevant Study: Dietary fiber, inflammation, and cardiovascular disease (King, 2005)

5. “Gravity Influences the Directional Growth of Plants”

Field: Agronomy / Botany

Type: Explanatory Hypothesis An explanatory hypothesis attempts to explain a phenomenon. In this case, the hypothesis proposes that gravity affects how plants direct their growth – both above-ground (toward sunlight) and below-ground (towards water and other resources).

The testing could be conducted by growing plants in a rotating cylinder to create artificial gravity.

Observations on the direction of growth, over a specified period, can provide insights into the influencing factors. If plants consistently direct their growth in a manner that indicates the influence of gravitational pull, the hypothesis is substantiated.

It is crucial to ensure that other growth-influencing factors, such as light and water, are uniformly distributed so that only gravity influences the directional growth.

6. “The Implementation of Gamified Learning Improves Students’ Motivation”

Field: Education

Type: Relational Hypothesis The relational hypothesis describes the relation between two variables. Here, the hypothesis is that the implementation of gamified learning has a positive effect on the motivation of students.

To validate this proposition, two sets of classes could be compared: one that implements a learning approach with game-based elements, and another that follows a traditional learning approach.

The students’ motivation levels could be gauged by monitoring their engagement, performance, and feedback over a considerable timeframe.

If the students engaged in the gamified learning context present higher levels of motivation and achievement, the hypothesis would be supported.

Control measures ought to be put into place to account for individual differences, including prior knowledge and attitudes towards learning.

Relevant Study: Does educational gamification improve students’ motivation? (Chapman & Rich, 2018)

7. “Mathematics Anxiety Negatively Affects Performance”

Field: Educational Psychology

Type: Research Hypothesis The research hypothesis involves making a prediction that will be tested. In this case, the hypothesis proposes that a student’s anxiety about math can negatively influence their performance in math-related tasks.

To assess this hypothesis, researchers must first measure the mathematics anxiety levels of a sample of students using a validated instrument, such as the Mathematics Anxiety Rating Scale.

Then, the students’ performance in mathematics would be evaluated through standard testing. If there’s a negative correlation between the levels of math anxiety and math performance (meaning as anxiety increases, performance decreases), the hypothesis would be supported.

It would be crucial to control for relevant factors such as overall academic performance and previous mathematical achievement.

8. “Disruption of Natural Sleep Cycle Impairs Worker Productivity”

Field: Organizational Psychology

Type: Operational Hypothesis The operational hypothesis involves defining the variables in measurable terms. In this example, the hypothesis posits that disrupting the natural sleep cycle, for instance through shift work or irregular working hours, can lessen productivity among workers.

To test this hypothesis, you could collect data from workers who maintain regular working hours and those with irregular schedules.

Measuring productivity could involve examining the worker’s ability to complete tasks, the quality of their work, and their efficiency.

If workers with interrupted sleep cycles demonstrate lower productivity compared to those with regular sleep patterns, it would lend support to the hypothesis.

Consideration should be given to potential confounding variables such as job type, worker age, and overall health.

9. “Regular Physical Activity Reduces the Risk of Depression”

Field: Health Psychology

Type: Predictive Hypothesis A predictive hypothesis involves making a prediction about the outcome of a study based on the observed relationship between variables. In this case, it is hypothesized that individuals who engage in regular physical activity are less likely to suffer from depression.

Longitudinal studies would suit to test this hypothesis, tracking participants’ levels of physical activity and their mental health status over time.

The level of physical activity could be self-reported or monitored, while mental health status could be assessed using standard diagnostic tools or surveys.

If data analysis shows that participants maintaining regular physical activity have a lower incidence of depression, this would endorse the hypothesis.

However, care should be taken to control other lifestyle and behavioral factors that could intervene with the results.

Relevant Study: Regular physical exercise and its association with depression (Kim, 2022)

10. “Regular Meditation Enhances Emotional Stability”

Type: Empirical Hypothesis In the empirical hypothesis, predictions are based on amassed empirical evidence . This particular hypothesis theorizes that frequent meditation leads to improved emotional stability, resonating with numerous studies linking meditation to a variety of psychological benefits.

Earlier studies reported some correlations, but to test this hypothesis directly, you’d organize an experiment where one group meditates regularly over a set period while a control group doesn’t.

Both groups’ emotional stability levels would be measured at the start and end of the experiment using a validated emotional stability assessment.

If regular meditators display noticeable improvements in emotional stability compared to the control group, the hypothesis gains credit.

You’d have to ensure a similar emotional baseline for all participants at the start to avoid skewed results.

11. “Children Exposed to Reading at an Early Age Show Superior Academic Progress”

Type: Directional Hypothesis The directional hypothesis predicts the direction of an expected relationship between variables. Here, the hypothesis anticipates that early exposure to reading positively affects a child’s academic advancement.

A longitudinal study tracking children’s reading habits from an early age and their consequent academic performance could validate this hypothesis.

Parents could report their children’s exposure to reading at home, while standardized school exam results would provide a measure of academic achievement.

If the children exposed to early reading consistently perform better acadically, it gives weight to the hypothesis.

However, it would be important to control for variables that might impact academic performance, such as socioeconomic background, parental education level, and school quality.

12. “Adopting Energy-efficient Technologies Reduces Carbon Footprint of Industries”

Field: Environmental Science

Type: Descriptive Hypothesis A descriptive hypothesis predicts the existence of an association or pattern related to variables. In this scenario, the hypothesis suggests that industries adopting energy-efficient technologies will resultantly show a reduced carbon footprint.

Global industries making use of energy-efficient technologies could track their carbon emissions over time. At the same time, others not implementing such technologies continue their regular tracking.

After a defined time, the carbon emission data of both groups could be compared. If industries that adopted energy-efficient technologies demonstrate a notable reduction in their carbon footprints, the hypothesis would hold strong.

In the experiment, you would exclude variations brought by factors such as industry type, size, and location.

13. “Reduced Screen Time Improves Sleep Quality”

Type: Simple Hypothesis The simple hypothesis is a prediction about the relationship between two variables, excluding any other variables from consideration. This example posits that by reducing time spent on devices like smartphones and computers, an individual should experience improved sleep quality.

A sample group would need to reduce their daily screen time for a pre-determined period. Sleep quality before and after the reduction could be measured using self-report sleep diaries and objective measures like actigraphy, monitoring movement and wakefulness during sleep.

If the data shows that sleep quality improved post the screen time reduction, the hypothesis would be validated.

Other aspects affecting sleep quality, like caffeine intake, should be controlled during the experiment.

Relevant Study: Screen time use impacts low‐income preschool children’s sleep quality, tiredness, and ability to fall asleep (Waller et al., 2021)

14. Engaging in Brain-Training Games Improves Cognitive Functioning in Elderly

Field: Gerontology

Type: Inductive Hypothesis Inductive hypotheses are based on observations leading to broader generalizations and theories. In this context, the hypothesis deduces from observed instances that engaging in brain-training games can help improve cognitive functioning in the elderly.

A longitudinal study could be conducted where an experimental group of elderly people partakes in regular brain-training games.

Their cognitive functioning could be assessed at the start of the study and at regular intervals using standard neuropsychological tests.

If the group engaging in brain-training games shows better cognitive functioning scores over time compared to a control group not playing these games, the hypothesis would be supported.

15. Farming Practices Influence Soil Erosion Rates

Type: Null Hypothesis A null hypothesis is a negative statement assuming no relationship or difference between variables. The hypothesis in this context asserts there’s no effect of different farming practices on the rates of soil erosion.

Comparing soil erosion rates in areas with different farming practices over a considerable timeframe could help test this hypothesis.

If, statistically, the farming practices do not lead to differences in soil erosion rates, the null hypothesis is accepted.

However, if marked variation appears, the null hypothesis is rejected, meaning farming practices do influence soil erosion rates. It would be crucial to control for external factors like weather, soil type, and natural vegetation.

The variety of hypotheses mentioned above underscores the diversity of research constructs inherent in different fields, each with its unique purpose and way of testing.

While researchers may develop hypotheses primarily as tools to define and narrow the focus of the study, these hypotheses also serve as valuable guiding forces for the data collection and analysis procedures, making the research process more efficient and direction-focused.

Hypotheses serve as a compass for any form of academic research. The diverse examples provided, from Psychology to Educational Studies, Environmental Science to Gerontology, clearly demonstrate how certain hypotheses suit specific fields more aptly than others.

It is important to underline that although these varied hypotheses differ in their structure and methods of testing, each endorses the fundamental value of empiricism in research. Evidence-based decision making remains at the heart of scholarly inquiry, regardless of the research field, thus aligning all hypotheses to the core purpose of scientific investigation.

Testing hypotheses is an essential part of the scientific method . By doing so, researchers can either confirm their predictions, giving further validity to an existing theory, or they might uncover new insights that could potentially shift the field’s understanding of a particular phenomenon. In either case, hypotheses serve as the stepping stones for scientific exploration and discovery.

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J. W., & Williams, R. A. (2021).  SAGE research methods foundations . SAGE Publications Ltd.

Curcio, G., Ferrara, M., & De Gennaro, L. (2006). Sleep loss, learning capacity and academic performance.  Sleep medicine reviews ,  10 (5), 323-337.

Kim, J. H. (2022). Regular physical exercise and its association with depression: A population-based study short title: Exercise and depression.  Psychiatry Research ,  309 , 114406.

King, D. E. (2005). Dietary fiber, inflammation, and cardiovascular disease.  Molecular nutrition & food research ,  49 (6), 594-600.

Marian, V., & Shook, A. (2012, September). The cognitive benefits of being bilingual. In Cerebrum: the Dana forum on brain science (Vol. 2012). Dana Foundation.

Tan, W. C. K. (2022). Research Methods: A Practical Guide For Students And Researchers (Second Edition) . World Scientific Publishing Company.

Waller, N. A., Zhang, N., Cocci, A. H., D’Agostino, C., Wesolek‐Greenson, S., Wheelock, K., … & Resnicow, K. (2021). Screen time use impacts low‐income preschool children’s sleep quality, tiredness, and ability to fall asleep. Child: care, health and development, 47 (5), 618-626.

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 10 Reasons you’re Perpetually Single
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 20 Montessori Toddler Bedrooms (Design Inspiration)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 21 Montessori Homeschool Setups
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 101 Hidden Talents Examples

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How to Write a Research Hypothesis: Good & Bad Examples

What is a research hypothesis?

A research hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. Hypotheses are sometimes called “educated guesses”, but they are in fact (or let’s say they should be) based on previous observations, existing theories, scientific evidence, and logic. A research hypothesis is also not a prediction—rather, predictions are ( should be) based on clearly formulated hypotheses. For example, “We tested the hypothesis that KLF2 knockout mice would show deficiencies in heart development” is an assumption or prediction, not a hypothesis. 

The research hypothesis at the basis of this prediction is “the product of the KLF2 gene is involved in the development of the cardiovascular system in mice”—and this hypothesis is probably (hopefully) based on a clear observation, such as that mice with low levels of Kruppel-like factor 2 (which KLF2 codes for) seem to have heart problems. From this hypothesis, you can derive the idea that a mouse in which this particular gene does not function cannot develop a normal cardiovascular system, and then make the prediction that we started with. 

What is the difference between a hypothesis and a prediction?

You might think that these are very subtle differences, and you will certainly come across many publications that do not contain an actual hypothesis or do not make these distinctions correctly. But considering that the formulation and testing of hypotheses is an integral part of the scientific method, it is good to be aware of the concepts underlying this approach. The two hallmarks of a scientific hypothesis are falsifiability (an evaluation standard that was introduced by the philosopher of science Karl Popper in 1934) and testability —if you cannot use experiments or data to decide whether an idea is true or false, then it is not a hypothesis (or at least a very bad one).

So, in a nutshell, you (1) look at existing evidence/theories, (2) come up with a hypothesis, (3) make a prediction that allows you to (4) design an experiment or data analysis to test it, and (5) come to a conclusion. Of course, not all studies have hypotheses (there is also exploratory or hypothesis-generating research), and you do not necessarily have to state your hypothesis as such in your paper. 

But for the sake of understanding the principles of the scientific method, let’s first take a closer look at the different types of hypotheses that research articles refer to and then give you a step-by-step guide for how to formulate a strong hypothesis for your own paper.

Types of Research Hypotheses

Hypotheses can be simple , which means they describe the relationship between one single independent variable (the one you observe variations in or plan to manipulate) and one single dependent variable (the one you expect to be affected by the variations/manipulation). If there are more variables on either side, you are dealing with a complex hypothesis. You can also distinguish hypotheses according to the kind of relationship between the variables you are interested in (e.g., causal or associative ). But apart from these variations, we are usually interested in what is called the “alternative hypothesis” and, in contrast to that, the “null hypothesis”. If you think these two should be listed the other way round, then you are right, logically speaking—the alternative should surely come second. However, since this is the hypothesis we (as researchers) are usually interested in, let’s start from there.

Alternative Hypothesis

If you predict a relationship between two variables in your study, then the research hypothesis that you formulate to describe that relationship is your alternative hypothesis (usually H1 in statistical terms). The goal of your hypothesis testing is thus to demonstrate that there is sufficient evidence that supports the alternative hypothesis, rather than evidence for the possibility that there is no such relationship. The alternative hypothesis is usually the research hypothesis of a study and is based on the literature, previous observations, and widely known theories. 

Null Hypothesis

The hypothesis that describes the other possible outcome, that is, that your variables are not related, is the null hypothesis ( H0 ). Based on your findings, you choose between the two hypotheses—usually that means that if your prediction was correct, you reject the null hypothesis and accept the alternative. Make sure, however, that you are not getting lost at this step of the thinking process: If your prediction is that there will be no difference or change, then you are trying to find support for the null hypothesis and reject H1. 

Directional Hypothesis

While the null hypothesis is obviously “static”, the alternative hypothesis can specify a direction for the observed relationship between variables—for example, that mice with higher expression levels of a certain protein are more active than those with lower levels. This is then called a one-tailed hypothesis. 

Another example for a directional one-tailed alternative hypothesis would be that 

H1: Attending private classes before important exams has a positive effect on performance. 

Your null hypothesis would then be that

H0: Attending private classes before important exams has no/a negative effect on performance.

Nondirectional Hypothesis

A nondirectional hypothesis does not specify the direction of the potentially observed effect, only that there is a relationship between the studied variables—this is called a two-tailed hypothesis. For instance, if you are studying a new drug that has shown some effects on pathways involved in a certain condition (e.g., anxiety) in vitro in the lab, but you can’t say for sure whether it will have the same effects in an animal model or maybe induce other/side effects that you can’t predict and potentially increase anxiety levels instead, you could state the two hypotheses like this:

H1: The only lab-tested drug (somehow) affects anxiety levels in an anxiety mouse model.

You then test this nondirectional alternative hypothesis against the null hypothesis:

H0: The only lab-tested drug has no effect on anxiety levels in an anxiety mouse model.

How to Write a Hypothesis for a Research Paper

Now that we understand the important distinctions between different kinds of research hypotheses, let’s look at a simple process of how to write a hypothesis.

Writing a Hypothesis Step:1

Ask a question, based on earlier research. Research always starts with a question, but one that takes into account what is already known about a topic or phenomenon. For example, if you are interested in whether people who have pets are happier than those who don’t, do a literature search and find out what has already been demonstrated. You will probably realize that yes, there is quite a bit of research that shows a relationship between happiness and owning a pet—and even studies that show that owning a dog is more beneficial than owning a cat ! Let’s say you are so intrigued by this finding that you wonder: 

What is it that makes dog owners even happier than cat owners? 

Let’s move on to Step 2 and find an answer to that question.

Writing a Hypothesis Step 2:

Formulate a strong hypothesis by answering your own question. Again, you don’t want to make things up, take unicorns into account, or repeat/ignore what has already been done. Looking at the dog-vs-cat papers your literature search returned, you see that most studies are based on self-report questionnaires on personality traits, mental health, and life satisfaction. What you don’t find is any data on actual (mental or physical) health measures, and no experiments. You therefore decide to make a bold claim come up with the carefully thought-through hypothesis that it’s maybe the lifestyle of the dog owners, which includes walking their dog several times per day, engaging in fun and healthy activities such as agility competitions, and taking them on trips, that gives them that extra boost in happiness. You could therefore answer your question in the following way:

Dog owners are happier than cat owners because of the dog-related activities they engage in.

Now you have to verify that your hypothesis fulfills the two requirements we introduced at the beginning of this resource article: falsifiability and testability . If it can’t be wrong and can’t be tested, it’s not a hypothesis. We are lucky, however, because yes, we can test whether owning a dog but not engaging in any of those activities leads to lower levels of happiness or well-being than owning a dog and playing and running around with them or taking them on trips.  

Writing a Hypothesis Step 3:

Make your predictions and define your variables. We have verified that we can test our hypothesis, but now we have to define all the relevant variables, design our experiment or data analysis, and make precise predictions. You could, for example, decide to study dog owners (not surprising at this point), let them fill in questionnaires about their lifestyle as well as their life satisfaction (as other studies did), and then compare two groups of active and inactive dog owners. Alternatively, if you want to go beyond the data that earlier studies produced and analyzed and directly manipulate the activity level of your dog owners to study the effect of that manipulation, you could invite them to your lab, select groups of participants with similar lifestyles, make them change their lifestyle (e.g., couch potato dog owners start agility classes, very active ones have to refrain from any fun activities for a certain period of time) and assess their happiness levels before and after the intervention. In both cases, your independent variable would be “ level of engagement in fun activities with dog” and your dependent variable would be happiness or well-being . 

Examples of a Good and Bad Hypothesis

Let’s look at a few examples of good and bad hypotheses to get you started.

Good Hypothesis Examples

Bad Hypothesis Examples

Tips for Writing a Research Hypothesis

If you understood the distinction between a hypothesis and a prediction we made at the beginning of this article, then you will have no problem formulating your hypotheses and predictions correctly. To refresh your memory: We have to (1) look at existing evidence, (2) come up with a hypothesis, (3) make a prediction, and (4) design an experiment. For example, you could summarize your dog/happiness study like this:

(1) While research suggests that dog owners are happier than cat owners, there are no reports on what factors drive this difference. (2) We hypothesized that it is the fun activities that many dog owners (but very few cat owners) engage in with their pets that increases their happiness levels. (3) We thus predicted that preventing very active dog owners from engaging in such activities for some time and making very inactive dog owners take up such activities would lead to an increase and decrease in their overall self-ratings of happiness, respectively. (4) To test this, we invited dog owners into our lab, assessed their mental and emotional well-being through questionnaires, and then assigned them to an “active” and an “inactive” group, depending on… 

Note that you use “we hypothesize” only for your hypothesis, not for your experimental prediction, and “would” or “if – then” only for your prediction, not your hypothesis. A hypothesis that states that something “would” affect something else sounds as if you don’t have enough confidence to make a clear statement—in which case you can’t expect your readers to believe in your research either. Write in the present tense, don’t use modal verbs that express varying degrees of certainty (such as may, might, or could ), and remember that you are not drawing a conclusion while trying not to exaggerate but making a clear statement that you then, in a way, try to disprove . And if that happens, that is not something to fear but an important part of the scientific process.

Similarly, don’t use “we hypothesize” when you explain the implications of your research or make predictions in the conclusion section of your manuscript, since these are clearly not hypotheses in the true sense of the word. As we said earlier, you will find that many authors of academic articles do not seem to care too much about these rather subtle distinctions, but thinking very clearly about your own research will not only help you write better but also ensure that even that infamous Reviewer 2 will find fewer reasons to nitpick about your manuscript. 

Perfect Your Manuscript With Professional Editing

Now that you know how to write a strong research hypothesis for your research paper, you might be interested in our free AI Proofreader , Wordvice AI, which finds and fixes errors in grammar, punctuation, and word choice in academic texts. Or if you are interested in human proofreading , check out our English editing services , including research paper editing and manuscript editing .

On the Wordvice academic resources website , you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.

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Physiology of sleep.

Joshua E. Brinkman ; Vamsi Reddy ; Sandeep Sharma .

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Last Update: April 3, 2023 .

• Introduction

Sleep is an extremely complicated process that consists of more than simply closing one’s eyelids and counting sheep.  It is an active state of unconsciousness produced by the body where the brain is in a relative state of rest and is reactive primarily to internal stimulus. The exact purpose of sleep has not been fully elucidated.  Several prominent theories have explored the brain and attempt to identify a purpose for why we sleep, which includes the Inactivity theory, Energy conservation theory, Restoration theory, and the Brain plasticity theory.

Inactivity theory is based on the concept of evolutionary pressure where creatures inactive at night were less likely to die from the predation of injury in the dark, thus creating an evolutionary and reproductive benefit to being inactive at night. 

Energy conservation theory posits that the main function of sleep is to reduce a person's energy demand during part of the day and night when it is least efficient to hunt for food. This theory is supported by the fact that the body has decreased metabolism by up to 10% during sleep.

The restorative theory states that sleep allows for the body to repair and replete cellular components necessary for biological functions that become depleted throughout an awake day. This is backed by the findings many functions in the body such as muscle repair, tissue growth, protein synthesis, and release of many of the important hormones for growth occur primarily during sleep.

Brain plasticity theory is that sleep is necessary for neural reorganization and growth of the brain’s structure and function. It is clear that sleep plays a role in the development of the brain in infants and children and explains why infants must sleep upwards of 14 hours per day.

These theories are not exhaustive or all-inclusive of the prevalent ideas; rather, they serve to frame the concept that we do not fully understand sleep yet. It is more accepted that no single theory explains it all, and a combination of these ideas is more likely to hold the key to sleep. [1] [2] [3] [4]

Sleep functions in a relatively predictable cyclical pattern between 2 major phases: Non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. NREM sleep is subdivided into several stages numbered 1 to 3. Each phase and stage represents the relative depth of sleep and offers unique characteristics in the brain wave, muscle tones, and eye movement patterns. As the name implies, NREM is characterized by an absence of eye movements, and rapid eye movements characterize REM.

Sleep begins with a short NREM stage 1 phase, followed by NREM stage 2, then NREM stage 3, then finally into REM. NREM accounts for approximately 75% to 80% of total sleep, and REM accounts for the remaining 20% to 25% of sleep. This progression through the stages of sleep occurs in this order of events on repeat throughout the night for varying lengths of time. The initial cycle lasts 70 to 100 minutes to complete fully. However, the remaining cycles last 90 to 120 minutes each. The amount of REM in each cycle progresses throughout the night from being minimal on the initiation of sleep but eventually is up to 30% of the cycle later in the night. A total of 4 to 5 cycles through this progression is typical in a night.

NREM stage 1 is the shallow stage of sleep where a person is still easily awoken. It lasts 1 to 7 minutes. Rhythmical alpha waves characterize electroencephalogram (EEG) at a frequency of 8 to 13 cycles per second.

NREM stage 2 lasts approximately 10 to 25 minutes in the initial cycle of sleep but progresses to consume 50% of the total sleep cycle later in the night. Stage 2 is a much deeper sleep state than stage 1, but individuals are still awoken with heavy stimulation. Brainwave activity on EEG is low voltage “sleep spindles and K-complexes.” Current theories suggest that memory consolidation occurs primarily during this stage.

NREM stage 3 lasts about 20 to 40 minutes, initially. EEG is characterized by high-voltage, slow-wave frequency.

REM is the phase of sleep responsible for dreaming. It is characterized by total body voluntary muscle paralysis (except for the extraocular muscles). This paralysis is thought to be a mechanism to prevent neural stimuli from dreams to manifest in actual muscular impulses during sleep. EEG in REM is “Sawtooth waveforms,” theta waves, and slow, alpha waves in a desynchronized pattern set. [5] [6]  Patients with nightmare disorder exhibit increased relative high alpha and frontocentral increases in high delta power during REM sleep.

The mechanism through which sleep is generated and maintained is more of a balance between two systems located within the brain: the homeostatic processes, which are functionally the body’s “need for sleep” center, and the circadian rhythm which is an internal clock for the sleep-wake cycle. 

Sleep Generation is initiated within the ventrolateral preoptic nucleus (VLPO) of the anterior hypothalamus and acts to inhibit the arousal regions of the brain, including the tuberomammillary nucleus, lateral hypothalamus, locus coeruleus, dorsal raphe, laterodorsal tegmental nucleus, and pedunculopontine tegmental nucleus. Hypocretin (orexin) neurons in the lateral hypothalamus help to facilitate this process in a synergistic effect.

NREM sleep is a functional disconnection between the brain stem and the thalamus and cortex maintained with hyperpolarizing GABA neurons in the reticular activating center of the thalamus and the cortex. Corticothalamic neurons signal the thalamus, which causes hyperpolarization of the thalamic reticular neurons.  This process produces delta waves from both thalamic reticular and cortical pyramidal sources. Thus correlating with the varying stages 1 to 3 of NREM.

REM sleep is generated by "REM-on neurons" in the mesencephalic and pontine cholinergic neurons. The pedunculopontine tegmental nucleus and the lateral dorsal tegmental neurons trigger desynchronized cortical waveforms. The tonic component of REM sleep is parasympathetically medicated, and the phasic component is sympathetically mediated.

Circadian rhythm is the body’s cyclical nature for the desire for sleep. The hypothalamus controls it via the suprachiasmatic nucleus with sensory input from the retinohypothalamic tract based on light levels detected from the retina. The circadian rhythm is approximately 24.2 hours per cycle. Melatonin, produced in the pineal gland, has also been shown to be a modulator of the circadian rhythm that has concentrations varied based on the light level. Melatonin levels are greatest at night and decrease during the daytime. Finally, body temperature has been associated as part of the circadian rhythm. The exact set point varies among different people, but it is expected to have generally lower temperatures in the morning and higher temperatures in the evening. [5] [7]

• Related Testing

The primary testing modality used to study sleep is polysomnography. This is a multifaceted test that includes an electrocardiogram (ECG), electroencephalography (EEG), electrooculography (EOG), electromyography (EMG), and oxygen saturation. Polysomnography should not be routinely used as a screening test. The results of all testing modalities are coordinated to paint a full picture of the sleeping status of a patient.

ECG testing is the measurement of electrical current through the myocardium of the breath and is used to diagnose cardiac aberrations, including rate and rhythm.

EEG includes non-invasively placing electrodes across the scalp to measure voltage fluctuations and current of electrical activity within the brain. The exact number of electrodes used varies.  The waveforms of the brain are recorded and used to interpret the stage of sleep a person is in and detect any neurological abnormalities during sleep.

EOG is used to measure extraocular muscle function during sleep.  During NREM, there should be no eye movement. Therefore eye movement is indicative of REM.

EMG is used to measure muscle function of respiration and peripheral limbs and can detect excessive movement or increased tension during sleep.

Oxygen saturation is used to verify that respiration is being performed as expected during sleep without any halts in breathing. [6] [8]

• Clinical Significance

This is the generic term for any illness that causes difficulty falling asleep and staying asleep. This is the most common of sleep illnesses and is commonly related to psychological stressors, poor sleeping environments, irregular sleep schedules, or excessive mental, physical, or chemical stimulation.

Obstructive Sleep Apnea

This is an illness where major pauses in breathing occur during sleep secondary to an obstructive process, such as the collapse of the airway secondary to obesity or weak pharyngeal musculature. When the airway collapses, breathing stops, and hypoxia drives the body to awaken out of deep sleep to breathe again. When this occurs regularly in the night, restful sleep is not possible. There are 3 degrees of illness with obstructive sleep apnea Mild, Moderate, and Severe. Mild OSA is when there are 5 to 14 episodes of apnea in an hour. Moderate is when there are 15 to 30 apnea episodes in an hour. Severe OSA is when there are 30 or more episodes of OSA in an hour. Positive airway pressure therapy characterizes the treatment of OSA: Continuous Positive Airway Pressure (CPAP) and Bilevel Positive Airway Pressure (BiPAP). CPAP is constant pressure supplementation that causes the airway to splint open, allowing for airflow. BiPAP is when the positive pressure supplementation is altered between 2 pressures allowing for the splinting benefit of positive pressure and allowing for better ventilation of the lung than CPAP. Also used as therapy are mandibular advancement devices and surgical therapy such as uvulopalatopharyngoplasty, adenotonsillectomy, and maxillomandibular advancement. Mainstream therapy is positive airway supplementation, not surgical. [9]

Central Sleep Apnea

This illness is similar to obstructive sleep apnea. However, its etiology is related to intrinsic diminution and ultimately failure of the breathing drive or mechanisms during sleep.  Such illnesses include congenital central hypoventilation syndrome (Ondine’s curse) or congestive heart failure.  When breathing does not occur effectively, the body will awaken from deep sleep to correct hypoxia. Treatment consists of CPAP therapy, BiPAP therapy, Adaptive-servo-ventilation, or medical therapy with acetazolamide or theophylline. [10]

Mixed Sleep Apnea (Complex Sleep Apnea)

It is a combination of both obstructive sleep apnea and central sleep apnea symptoms. This is an illness where patients with symptoms of obstructive sleep apnea develop symptoms of central sleep apnea upon treatment with CPAP therapy during a sleep study. Treatment is typically very low-pressure CPAP therapy. [11]

Ghrelin-Leptin Abnormalities

Sleep duration has been found to play a significant role in maintaining body weight. The theory here is that an imbalance in the two essential hormones related to hunger (Leptin and Ghrelin) is aberrant with altered sleep habits. Leptin is made by adipose cells and functions to regulate energy balance by inhibiting the hunger drive. Ghrelin is the counter-regulatory hormone to leptin produced by cholinergic cells in the gastrointestinal tract and is responsible for increasing appetite, thus encouraging the hunger drive. Shorter nights of sleep are associated with reduced leptin and elevated ghrelin. These differences in leptin and ghrelin likely lead to increased appetite, possibly explaining the increased BMI observed with sleepless nights.   This aberration is commonly associated with OSA because of the fact that increased BMI is directly related to the development of OSA. The treatment here is to sleep consistently 7 to 8 hours per night. [12]

Narcolepsy type 1 occurs when nearly all of the neurons that contain orexin (also called hypocretin) are lost. The mechanism of narcolepsy type 2 is less clear, but it is thought that it may be due to a similar but less severe loss of orexin neurons. During normal REM sleep, orexin decreases, which decreases RAS activity and promotes atonia. In narcolepsy type 1, the mechanism that separates wake from sleep becomes unstable without sufficient levels of orexin. The RAS no longer consistently causes the release of wake-promoting neurotransmitters to the cortex and inconsistently inhibits the VLPO. This results in rapid transitions between sleep and wake and allows the intrusion of REM-related phenomena into wakefulness. This is characterized by episodes of daytime somnolence, cataplexy, and occasionally hallucinations throughout the day that extreme emotions may trigger.  Many people with narcolepsy also suffer from insomnia. [13]

Somnambulism

A state of combined sleep and wakefulness that leads to sleep-walking. Sleepwalking is when a person ambulates or performs actions without consciously controlling the movement or having a memory of the event.  This illness is not fully understood, but it has been associated with increased slow-wave sleep and sleep deprivation, and there is evidence that there is a genetic component of inheritance. Mainstay therapy consists of benzodiazepines. [6] [14]

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Disclosure: Joshua Brinkman declares no relevant financial relationships with ineligible companies.

Disclosure: Vamsi Reddy declares no relevant financial relationships with ineligible companies.

Disclosure: Sandeep Sharma declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

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What Is a Hypothesis and How Do I Write One?

General Education

Think about something strange and unexplainable in your life. Maybe you get a headache right before it rains, or maybe you think your favorite sports team wins when you wear a certain color. If you wanted to see whether these are just coincidences or scientific fact, you would form a hypothesis, then create an experiment to see whether that hypothesis is true or not.

But what is a hypothesis, anyway? If you’re not sure about what a hypothesis is--or how to test for one!--you’re in the right place. This article will teach you everything you need to know about hypotheses, including: 

• Defining the term “hypothesis” 
• Providing hypothesis examples 
• Giving you tips for how to write your own hypothesis

So let’s get started!

What Is a Hypothesis?

Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess . Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable. You have to be able to design an experiment that tests your hypothesis in order for it to be valid. 

As you could assume from that statement, it’s easy to make a bad hypothesis. But when you’re holding an experiment, it’s even more important that your guesses be good...after all, you’re spending time (and maybe money!) to figure out more about your observation. That’s why we refer to a hypothesis as an educated guess--good hypotheses are based on existing data and research to make them as sound as possible.

Hypotheses are one part of what’s called the scientific method .  Every (good) experiment or study is based in the scientific method. The scientific method gives order and structure to experiments and ensures that interference from scientists or outside influences does not skew the results. It’s important that you understand the concepts of the scientific method before holding your own experiment. Though it may vary among scientists, the scientific method is generally made up of six steps (in order):

• Observation
• Asking questions
• Forming a hypothesis
• Analyze the data
• Communicate your results

You’ll notice that the hypothesis comes pretty early on when conducting an experiment. That’s because experiments work best when they’re trying to answer one specific question. And you can’t conduct an experiment until you know what you’re trying to prove!

Independent and Dependent Variables 

After doing your research, you’re ready for another important step in forming your hypothesis: identifying variables. Variables are basically any factor that could influence the outcome of your experiment . Variables have to be measurable and related to the topic being studied.

There are two types of variables:  independent variables and dependent variables. I ndependent variables remain constant . For example, age is an independent variable; it will stay the same, and researchers can look at different ages to see if it has an effect on the dependent variable. 

Speaking of dependent variables... dependent variables are subject to the influence of the independent variable , meaning that they are not constant. Let’s say you want to test whether a person’s age affects how much sleep they need. In that case, the independent variable is age (like we mentioned above), and the dependent variable is how much sleep a person gets. 

Variables will be crucial in writing your hypothesis. You need to be able to identify which variable is which, as both the independent and dependent variables will be written into your hypothesis. For instance, in a study about exercise, the independent variable might be the speed at which the respondents walk for thirty minutes, and the dependent variable would be their heart rate. In your study and in your hypothesis, you’re trying to understand the relationship between the two variables.

Elements of a Good Hypothesis

The best hypotheses start by asking the right questions . For instance, if you’ve observed that the grass is greener when it rains twice a week, you could ask what kind of grass it is, what elevation it’s at, and if the grass across the street responds to rain in the same way. Any of these questions could become the backbone of experiments to test why the grass gets greener when it rains fairly frequently.

As you’re asking more questions about your first observation, make sure you’re also making more observations . If it doesn’t rain for two weeks and the grass still looks green, that’s an important observation that could influence your hypothesis. You'll continue observing all throughout your experiment, but until the hypothesis is finalized, every observation should be noted.

Finally, you should consult secondary research before writing your hypothesis . Secondary research is comprised of results found and published by other people. You can usually find this information online or at your library. Additionally, m ake sure the research you find is credible and related to your topic. If you’re studying the correlation between rain and grass growth, it would help you to research rain patterns over the past twenty years for your county, published by a local agricultural association. You should also research the types of grass common in your area, the type of grass in your lawn, and whether anyone else has conducted experiments about your hypothesis. Also be sure you’re checking the quality of your research . Research done by a middle school student about what minerals can be found in rainwater would be less useful than an article published by a local university.

Writing Your Hypothesis

Once you’ve considered all of the factors above, you’re ready to start writing your hypothesis. Hypotheses usually take a certain form when they’re written out in a research report.

When you boil down your hypothesis statement, you are writing down your best guess and not the question at hand . This means that your statement should be written as if it is fact already, even though you are simply testing it.

The reason for this is that, after you have completed your study, you'll either accept or reject your if-then or your null hypothesis. All hypothesis testing examples should be measurable and able to be confirmed or denied. You cannot confirm a question, only a statement! 

In fact, you come up with hypothesis examples all the time! For instance, when you guess on the outcome of a basketball game, you don’t say, “Will the Miami Heat beat the Boston Celtics?” but instead, “I think the Miami Heat will beat the Boston Celtics.” You state it as if it is already true, even if it turns out you’re wrong. You do the same thing when writing your hypothesis.

Additionally, keep in mind that hypotheses can range from very specific to very broad.  These hypotheses can be specific, but if your hypothesis testing examples involve a broad range of causes and effects, your hypothesis can also be broad.  

The Two Types of Hypotheses

Now that you understand what goes into a hypothesis, it’s time to look more closely at the two most common types of hypothesis: the if-then hypothesis and the null hypothesis.

#1: If-Then Hypotheses

First of all, if-then hypotheses typically follow this formula:

If ____ happens, then ____ will happen.

The goal of this type of hypothesis is to test the causal relationship between the independent and dependent variable. It’s fairly simple, and each hypothesis can vary in how detailed it can be. We create if-then hypotheses all the time with our daily predictions. Here are some examples of hypotheses that use an if-then structure from daily life: 

• If I get enough sleep, I’ll be able to get more work done tomorrow.
• If the bus is on time, I can make it to my friend’s birthday party. 
• If I study every night this week, I’ll get a better grade on my exam. 

In each of these situations, you’re making a guess on how an independent variable (sleep, time, or studying) will affect a dependent variable (the amount of work you can do, making it to a party on time, or getting better grades). 

You may still be asking, “What is an example of a hypothesis used in scientific research?” Take one of the hypothesis examples from a real-world study on whether using technology before bed affects children’s sleep patterns. The hypothesis read s:

“We hypothesized that increased hours of tablet- and phone-based screen time at bedtime would be inversely correlated with sleep quality and child attention.”

It might not look like it, but this is an if-then statement. The researchers basically said, “If children have more screen usage at bedtime, then their quality of sleep and attention will be worse.” The sleep quality and attention are the dependent variables and the screen usage is the independent variable. (Usually, the independent variable comes after the “if” and the dependent variable comes after the “then,” as it is the independent variable that affects the dependent variable.) This is an excellent example of how flexible hypothesis statements can be, as long as the general idea of “if-then” and the independent and dependent variables are present.

#2: Null Hypotheses

Your if-then hypothesis is not the only one needed to complete a successful experiment, however. You also need a null hypothesis to test it against. In its most basic form, the null hypothesis is the opposite of your if-then hypothesis . When you write your null hypothesis, you are writing a hypothesis that suggests that your guess is not true, and that the independent and dependent variables have no relationship .

One null hypothesis for the cell phone and sleep study from the last section might say: 

“If children have more screen usage at bedtime, their quality of sleep and attention will not be worse.” 

In this case, this is a null hypothesis because it’s asking the opposite of the original thesis! 

Conversely, if your if-then hypothesis suggests that your two variables have no relationship, then your null hypothesis would suggest that there is one. So, pretend that there is a study that is asking the question, “Does the amount of followers on Instagram influence how long people spend on the app?” The independent variable is the amount of followers, and the dependent variable is the time spent. But if you, as the researcher, don’t think there is a relationship between the number of followers and time spent, you might write an if-then hypothesis that reads:

“If people have many followers on Instagram, they will not spend more time on the app than people who have less.”

In this case, the if-then suggests there isn’t a relationship between the variables. In that case, one of the null hypothesis examples might say:

“If people have many followers on Instagram, they will spend more time on the app than people who have less.”

You then test both the if-then and the null hypothesis to gauge if there is a relationship between the variables, and if so, how much of a relationship. 

4 Tips to Write the Best Hypothesis

If you’re going to take the time to hold an experiment, whether in school or by yourself, you’re also going to want to take the time to make sure your hypothesis is a good one. The best hypotheses have four major elements in common: plausibility, defined concepts, observability, and general explanation.

#1: Plausibility

At first glance, this quality of a hypothesis might seem obvious. When your hypothesis is plausible, that means it’s possible given what we know about science and general common sense. However, improbable hypotheses are more common than you might think. 

Imagine you’re studying weight gain and television watching habits. If you hypothesize that people who watch more than  twenty hours of television a week will gain two hundred pounds or more over the course of a year, this might be improbable (though it’s potentially possible). Consequently, c ommon sense can tell us the results of the study before the study even begins.

Improbable hypotheses generally go against  science, as well. Take this hypothesis example: 

“If a person smokes one cigarette a day, then they will have lungs just as healthy as the average person’s.” 

This hypothesis is obviously untrue, as studies have shown again and again that cigarettes negatively affect lung health. You must be careful that your hypotheses do not reflect your own personal opinion more than they do scientifically-supported findings. This plausibility points to the necessity of research before the hypothesis is written to make sure that your hypothesis has not already been disproven.

#2: Defined Concepts

The more advanced you are in your studies, the more likely that the terms you’re using in your hypothesis are specific to a limited set of knowledge. One of the hypothesis testing examples might include the readability of printed text in newspapers, where you might use words like “kerning” and “x-height.” Unless your readers have a background in graphic design, it’s likely that they won’t know what you mean by these terms. Thus, it’s important to either write what they mean in the hypothesis itself or in the report before the hypothesis.

Here’s what we mean. Which of the following sentences makes more sense to the common person?

If the kerning is greater than average, more words will be read per minute.

If the space between letters is greater than average, more words will be read per minute.

For people reading your report that are not experts in typography, simply adding a few more words will be helpful in clarifying exactly what the experiment is all about. It’s always a good idea to make your research and findings as accessible as possible. 

Good hypotheses ensure that you can observe the results. 

#3: Observability

In order to measure the truth or falsity of your hypothesis, you must be able to see your variables and the way they interact. For instance, if your hypothesis is that the flight patterns of satellites affect the strength of certain television signals, yet you don’t have a telescope to view the satellites or a television to monitor the signal strength, you cannot properly observe your hypothesis and thus cannot continue your study.

Some variables may seem easy to observe, but if you do not have a system of measurement in place, you cannot observe your hypothesis properly. Here’s an example: if you’re experimenting on the effect of healthy food on overall happiness, but you don’t have a way to monitor and measure what “overall happiness” means, your results will not reflect the truth. Monitoring how often someone smiles for a whole day is not reasonably observable, but having the participants state how happy they feel on a scale of one to ten is more observable. 

In writing your hypothesis, always keep in mind how you'll execute the experiment.

#4: Generalizability 

Perhaps you’d like to study what color your best friend wears the most often by observing and documenting the colors she wears each day of the week. This might be fun information for her and you to know, but beyond you two, there aren’t many people who could benefit from this experiment. When you start an experiment, you should note how generalizable your findings may be if they are confirmed. Generalizability is basically how common a particular phenomenon is to other people’s everyday life.

Let’s say you’re asking a question about the health benefits of eating an apple for one day only, you need to realize that the experiment may be too specific to be helpful. It does not help to explain a phenomenon that many people experience. If you find yourself with too specific of a hypothesis, go back to asking the big question: what is it that you want to know, and what do you think will happen between your two variables?

Hypothesis Testing Examples

We know it can be hard to write a good hypothesis unless you’ve seen some good hypothesis examples. We’ve included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses.

Experiment #1: Students Studying Outside (Writing a Hypothesis)

You are a student at PrepScholar University. When you walk around campus, you notice that, when the temperature is above 60 degrees, more students study in the quad. You want to know when your fellow students are more likely to study outside. With this information, how do you make the best hypothesis possible?

You must remember to make additional observations and do secondary research before writing your hypothesis. In doing so, you notice that no one studies outside when it’s 75 degrees and raining, so this should be included in your experiment. Also, studies done on the topic beforehand suggested that students are more likely to study in temperatures less than 85 degrees. With this in mind, you feel confident that you can identify your variables and write your hypotheses:

If-then: “If the temperature in Fahrenheit is less than 60 degrees, significantly fewer students will study outside.”

Null: “If the temperature in Fahrenheit is less than 60 degrees, the same number of students will study outside as when it is more than 60 degrees.”

These hypotheses are plausible, as the temperatures are reasonably within the bounds of what is possible. The number of people in the quad is also easily observable. It is also not a phenomenon specific to only one person or at one time, but instead can explain a phenomenon for a broader group of people.

To complete this experiment, you pick the month of October to observe the quad. Every day (except on the days where it’s raining)from 3 to 4 PM, when most classes have released for the day, you observe how many people are on the quad. You measure how many people come  and how many leave. You also write down the temperature on the hour. 

After writing down all of your observations and putting them on a graph, you find that the most students study on the quad when it is 70 degrees outside, and that the number of students drops a lot once the temperature reaches 60 degrees or below. In this case, your research report would state that you accept or “failed to reject” your first hypothesis with your findings.

Experiment #2: The Cupcake Store (Forming a Simple Experiment)

Let’s say that you work at a bakery. You specialize in cupcakes, and you make only two colors of frosting: yellow and purple. You want to know what kind of customers are more likely to buy what kind of cupcake, so you set up an experiment. Your independent variable is the customer’s gender, and the dependent variable is the color of the frosting. What is an example of a hypothesis that might answer the question of this study?

Here’s what your hypotheses might look like: 

If-then: “If customers’ gender is female, then they will buy more yellow cupcakes than purple cupcakes.”

Null: “If customers’ gender is female, then they will be just as likely to buy purple cupcakes as yellow cupcakes.”

This is a pretty simple experiment! It passes the test of plausibility (there could easily be a difference), defined concepts (there’s nothing complicated about cupcakes!), observability (both color and gender can be easily observed), and general explanation ( this would potentially help you make better business decisions ).

Experiment #3: Backyard Bird Feeders (Integrating Multiple Variables and Rejecting the If-Then Hypothesis)

While watching your backyard bird feeder, you realized that different birds come on the days when you change the types of seeds. You decide that you want to see more cardinals in your backyard, so you decide to see what type of food they like the best and set up an experiment. 

However, one morning, you notice that, while some cardinals are present, blue jays are eating out of your backyard feeder filled with millet. You decide that, of all of the other birds, you would like to see the blue jays the least. This means you'll have more than one variable in your hypothesis. Your new hypotheses might look like this: 

If-then: “If sunflower seeds are placed in the bird feeders, then more cardinals will come than blue jays. If millet is placed in the bird feeders, then more blue jays will come than cardinals.”

Null: “If either sunflower seeds or millet are placed in the bird, equal numbers of cardinals and blue jays will come.”

Through simple observation, you actually find that cardinals come as often as blue jays when sunflower seeds or millet is in the bird feeder. In this case, you would reject your “if-then” hypothesis and “fail to reject” your null hypothesis . You cannot accept your first hypothesis, because it’s clearly not true. Instead you found that there was actually no relation between your different variables. Consequently, you would need to run more experiments with different variables to see if the new variables impact the results.

Experiment #4: In-Class Survey (Including an Alternative Hypothesis)

You’re about to give a speech in one of your classes about the importance of paying attention. You want to take this opportunity to test a hypothesis you’ve had for a while: 

If-then: If students sit in the first two rows of the classroom, then they will listen better than students who do not.

Null: If students sit in the first two rows of the classroom, then they will not listen better or worse than students who do not.

You give your speech and then ask your teacher if you can hand out a short survey to the class. On the survey, you’ve included questions about some of the topics you talked about. When you get back the results, you’re surprised to see that not only do the students in the first two rows not pay better attention, but they also scored worse than students in other parts of the classroom! Here, both your if-then and your null hypotheses are not representative of your findings. What do you do?

This is when you reject both your if-then and null hypotheses and instead create an alternative hypothesis . This type of hypothesis is used in the rare circumstance that neither of your hypotheses is able to capture your findings . Now you can use what you’ve learned to draft new hypotheses and test again! 

Key Takeaways: Hypothesis Writing

The more comfortable you become with writing hypotheses, the better they will become. The structure of hypotheses is flexible and may need to be changed depending on what topic you are studying. The most important thing to remember is the purpose of your hypothesis and the difference between the if-then and the null . From there, in forming your hypothesis, you should constantly be asking questions, making observations, doing secondary research, and considering your variables. After you have written your hypothesis, be sure to edit it so that it is plausible, clearly defined, observable, and helpful in explaining a general phenomenon.

Writing a hypothesis is something that everyone, from elementary school children competing in a science fair to professional scientists in a lab, needs to know how to do. Hypotheses are vital in experiments and in properly executing the scientific method . When done correctly, hypotheses will set up your studies for success and help you to understand the world a little better, one experiment at a time.

What’s Next?

If you’re studying for the science portion of the ACT, there’s definitely a lot you need to know. We’ve got the tools to help, though! Start by checking out our ultimate study guide for the ACT Science subject test. Once you read through that, be sure to download our recommended ACT Science practice tests , since they’re one of the most foolproof ways to improve your score. (And don’t forget to check out our expert guide book , too.)

If you love science and want to major in a scientific field, you should start preparing in high school . Here are the science classes you should take to set yourself up for success.

If you’re trying to think of science experiments you can do for class (or for a science fair!), here’s a list of 37 awesome science experiments you can do at home

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Ashley Sufflé Robinson has a Ph.D. in 19th Century English Literature. As a content writer for PrepScholar, Ashley is passionate about giving college-bound students the in-depth information they need to get into the school of their dreams.

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What Is a Hypothesis? (Science)

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A hypothesis (plural hypotheses) is a proposed explanation for an observation. The definition depends on the subject.

In science, a hypothesis is part of the scientific method. It is a prediction or explanation that is tested by an experiment. Observations and experiments may disprove a scientific hypothesis, but can never entirely prove one.

In the study of logic, a hypothesis is an if-then proposition, typically written in the form, "If X , then Y ."

In common usage, a hypothesis is simply a proposed explanation or prediction, which may or may not be tested.

Writing a Hypothesis

Most scientific hypotheses are proposed in the if-then format because it's easy to design an experiment to see whether or not a cause and effect relationship exists between the independent variable and the dependent variable . The hypothesis is written as a prediction of the outcome of the experiment.

Null Hypothesis and Alternative Hypothesis

Statistically, it's easier to show there is no relationship between two variables than to support their connection. So, scientists often propose the null hypothesis . The null hypothesis assumes changing the independent variable will have no effect on the dependent variable.

In contrast, the alternative hypothesis suggests changing the independent variable will have an effect on the dependent variable. Designing an experiment to test this hypothesis can be trickier because there are many ways to state an alternative hypothesis.

For example, consider a possible relationship between getting a good night's sleep and getting good grades. The null hypothesis might be stated: "The number of hours of sleep students get is unrelated to their grades" or "There is no correlation between hours of sleep and grades."

An experiment to test this hypothesis might involve collecting data, recording average hours of sleep for each student and grades. If a student who gets eight hours of sleep generally does better than students who get four hours of sleep or 10 hours of sleep, the hypothesis might be rejected.

But the alternative hypothesis is harder to propose and test. The most general statement would be: "The amount of sleep students get affects their grades." The hypothesis might also be stated as "If you get more sleep, your grades will improve" or "Students who get nine hours of sleep have better grades than those who get more or less sleep."

In an experiment, you can collect the same data, but the statistical analysis is less likely to give you a high confidence limit.

Usually, a scientist starts out with the null hypothesis. From there, it may be possible to propose and test an alternative hypothesis, to narrow down the relationship between the variables.

Example of a Hypothesis

Examples of a hypothesis include:

• If you drop a rock and a feather, (then) they will fall at the same rate.
• Plants need sunlight in order to live. (if sunlight, then life)
• Eating sugar gives you energy. (if sugar, then energy)
• White, Jay D.  Research in Public Administration . Conn., 1998.
• Schick, Theodore, and Lewis Vaughn.  How to Think about Weird Things: Critical Thinking for a New Age . McGraw-Hill Higher Education, 2002.
• Scientific Method Flow Chart
• Six Steps of the Scientific Method
• What Are the Elements of a Good Hypothesis?
• What Are Examples of a Hypothesis?
• What Is a Testable Hypothesis?
• Null Hypothesis Examples
• Scientific Hypothesis Examples
• Scientific Variable
• Scientific Method Vocabulary Terms
• Understanding Simple vs Controlled Experiments
• What Is an Experimental Constant?
• What Is a Controlled Experiment?
• What Is the Difference Between a Control Variable and Control Group?
• DRY MIX Experiment Variables Acronym
• Random Error vs. Systematic Error
• The Role of a Controlled Variable in an Experiment

Simple Hypothesis

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Venturing into the realm of scientific inquiry, the hypothesis stands as a beacon, guiding researchers towards answers. A simple hypothesis, crisp and to the point, paves the way for clear testing and straightforward results. But how does one draft such a potent statement? And what makes it so effective? Join us as we demystify the art of creating simple hypothesis statements and share invaluable tips to refine your approach.”

What is an example of a Simple hypothesis statement?

A simple hypothesis statement typically specifies a relationship or difference between two variables. Here’s an example:

Caffeine Consumption and Alertness: Consuming caffeine increases a person’s alertness.

In this example, the two variables are “caffeine consumption” and “alertness.” The hypothesis simply posits that there’s a direct relationship between these two variables, indicating that as one (caffeine consumption) increases, the other (alertness) does as well.

100 Simple Hypothesis Statement Examples

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Simple hypothesis statements act as the backbone of research, succinctly proposing a direct relationship or difference between two variables. These straightforward declarations pave the way for clear testing and results, offering a digestible insight into expected outcomes.

• Sunlight and Plant Growth : Exposure to sunlight increases plant growth.
• Reading and Vocabulary Expansion : Regular reading leads to an expanded vocabulary.
• Exercise and Heart Health : Engaging in exercise improves heart health.
• Sugar Intake and Energy Levels : Consuming sugar temporarily boosts energy levels.
• Hydration and Skin Health : Drinking water improves skin hydration.
• Meditation and Stress Reduction : Practicing meditation reduces stress levels.
• Music and Productivity : Listening to music enhances work productivity.
• Sleep Duration and Cognitive Functions : Getting adequate sleep improves cognitive functions.
• Fertilizer and Crop Yield : Using fertilizers increases crop yields.
• Probiotics and Gut Health : Consuming probiotics enhances gut health.
• Screen Time and Eye Strain : Prolonged screen time leads to increased eye strain.
• Social Media Usage and Loneliness : Frequent social media use is linked to feelings of loneliness.
• Carbon Emissions and Global Warming : Higher carbon emissions contribute to global warming.
• Vitamin C and Immunity : Consuming vitamin C boosts immune functions.
• Artificial Lights and Sleep Quality : Exposure to artificial lights at night reduces sleep quality.
• Yoga and Flexibility : Regular yoga practice increases flexibility.
• Chocolate Consumption and Mood : Eating chocolate elevates mood.
• Brushing and Dental Health : Regular brushing reduces dental cavities.
• Temperature and Metabolism Rate : Cold environments accelerate metabolism.
• Pet Ownership and Happiness : Having a pet contributes to increased happiness levels.
• Puzzles and Brain Activity : Solving puzzles activates brain functions.
• Green Tea and Weight Loss : Drinking green tea aids in weight loss.
• Salt Intake and Blood Pressure : Consuming high amounts of salt raises blood pressure.
• Indoor Plants and Air Quality : Having indoor plants improves air quality.
• Antibiotics and Bacterial Infections : Taking antibiotics reduces bacterial infections.
• Laughter and Endorphin Release : Engaging in laughter releases endorphins.
• Gaming and Hand-Eye Coordination : Playing video games improves hand-eye coordination.
• Washing Hands and Germ Spread : Regular hand washing reduces the spread of germs.
• Spicy Foods and Metabolism : Consuming spicy foods boosts metabolism.
• Journaling and Emotional Health : Maintaining a journal aids emotional well-being.
• Urban Areas and Noise Pollution : Urban regions are associated with higher noise pollution.
• Physical Activity and Bone Density : Regular physical activity strengthens bone density.
• Aloe Vera and Skin Soothing : Applying aloe vera soothes skin irritations.
• Alcohol Consumption and Reaction Time : Drinking alcohol slows down reaction time.
• Bird Watching and Patience : Engaging in bird watching cultivates patience.
• Cycling and Leg Strength : Regular cycling enhances leg muscle strength.
• Public Speaking and Confidence : Practicing public speaking boosts confidence.
• Dancing and Cardiovascular Health : Dancing regularly improves cardiovascular health.
• Acupuncture and Pain Relief : Undergoing acupuncture reduces pain.
• Caloric Restriction and Lifespan : Reducing caloric intake is linked to extended lifespan.
• Olive Oil and Heart Health : Consuming olive oil promotes heart health.
• Mindfulness and Attention Span : Practicing mindfulness increases attention span.
• Bilingualism and Cognitive Flexibility : Being bilingual enhances cognitive flexibility.
• Heavy Metals and Water Toxicity : Presence of heavy metals increases water toxicity.
• Mountain Climbing and Stamina : Engaging in mountain climbing builds stamina.
• Urbanization and Wildlife Displacement : Increased urbanization leads to wildlife displacement.
• Mentoring and Career Progression : Having a mentor accelerates career progression.
• Organic Farming and Soil Health : Practicing organic farming enhances soil health.
• Red Wine and Antioxidant Intake : Consuming red wine increases antioxidant intake.
• Studying Abroad and Cultural Awareness : Studying abroad enhances cultural awareness.
• E-books and Reading Duration : Using e-books extends reading duration.
• Swimming and Lung Capacity : Regular swimming increases lung capacity.
• Deforestation and Carbon Dioxide Levels : Deforestation raises carbon dioxide levels.
• Fast Food and Obesity : Frequent fast food consumption is linked to obesity.
• Classical Music and Infant Sleep : Playing classical music improves infant sleep duration.
• Microplastics and Marine Pollution : The presence of microplastics heightens marine pollution.
• Afforestation and Rainfall : Increasing forest cover can lead to higher rainfall.
• Gratitude Journaling and Positivity : Maintaining a gratitude journal boosts feelings of positivity.
• Singing and Lung Function : Regular singing enhances lung function.
• Noise Pollution and Stress : Exposure to noise pollution increases stress levels.
• Rural Living and Mental Peace : Living in rural areas promotes mental peace.
• Soft Drinks and Bone Density : Consuming soft drinks decreases bone density.
• Travel and Open-mindedness : Traveling frequently fosters open-mindedness.
• Digital Learning and Student Engagement : Digital learning tools increase student engagement.
• Plastic Usage and Land Pollution : Increased plastic usage contributes to land pollution.
• Stretching and Muscle Flexibility : Daily stretching improves muscle flexibility.
• Wine Consumption and Gut Health : Moderate wine consumption benefits gut health.
• Homework and Academic Achievement : Regular homework boosts academic achievement.
• Raw Foods and Digestive Health : Consuming raw foods aids digestive health.
• High Heels and Posture : Wearing high heels affects posture negatively.
• Therapy and Mental Well-being : Engaging in therapy promotes mental well-being.
• Fast Charging and Battery Lifespan : Using fast charging can reduce battery lifespan.
• Pottery and Hand Dexterity : Practicing pottery improves hand dexterity.
• Group Study and Retention : Studying in groups enhances information retention.
• Red Meat and Cholesterol Levels : Consuming red meat increases cholesterol levels.
• Kombucha and Gut Flora : Drinking kombucha benefits gut flora.
• Night Driving and Accident Risk : Driving at night increases the risk of accidents.
• Karaoke and Social Bonding : Engaging in karaoke fosters social bonding.
• Balanced Diet and Energy Levels : Following a balanced diet boosts energy levels.
• Multitasking and Task Efficiency : Multitasking reduces task efficiency.
• Gardening and Stress Relief : Regular gardening acts as a stress reliever.
• Digital Detox and Sleep Quality : Undertaking a digital detox improves sleep quality.
• Massage and Muscle Relaxation : Getting massages aids muscle relaxation.
• Animal Therapy and Emotional Healing : Engaging with animals accelerates emotional healing.
• Crafting and Creativity : Regular crafting activities enhance creativity.
• Organ Donation and Life-saving : Organ donation can be life-saving.
• Bamboo Products and Sustainability : Using bamboo products promotes sustainability.
• Weight Training and Muscle Mass : Engaging in weight training increases muscle mass.
• Fermented Foods and Digestion : Consuming fermented foods aids digestion.
• Outdoor Activities and Vitamin D Levels : Engaging in outdoor activities boosts Vitamin D levels.
• Smoking and Lung Health : Regular smoking deteriorates lung health.
• Feedback and Performance Improvement : Receiving feedback improves performance.
• Adventure Sports and Risk-taking Ability : Engaging in adventure sports enhances risk-taking ability.
• Coding and Logical Thinking : Learning to code promotes logical thinking.
• Chocolate and Antioxidant Levels : Eating dark chocolate boosts antioxidant levels.
• Vegetarian Diet and Heart Health : Following a vegetarian diet improves heart health.
• Deep Breathing and Relaxation : Practicing deep breathing induces relaxation.
• Natural Light and Productivity : Exposure to natural light enhances productivity.
• Green Spaces and Mental Health : Access to green spaces boosts mental well-being.
• Recycling and Resource Conservation : Regular recycling promotes resource conservation.

Simple Hypothesis Statement Examples for Kids

Kids often view the world with endless curiosity. Simplified hypotheses allow them to test their surroundings and grasp scientific methods. These Hypothesis for kids statements, tailored for young inquisitors, provide clear cause-and-effect scenarios to foster their learning.

• Ice Melting : Placing ice in the sun will make it melt faster than in the shade.
• Plant Growth : Plants kept near the window grow taller than plants in dark corners.
• Pet’s Activity : Dogs are more active during the day than at night.
• Toy Durability : Soft toys tear more easily than hard plastic toys.
• Sleep Patterns : Going to bed late makes you feel more tired the next morning.
• Food Preference : Cats prefer fish-flavored food over chicken-flavored food.
• Shadow Formation : Standing against the light creates longer shadows during the evening.
• Bubble Size : Using more soap in water creates bigger bubbles.
• Learning Speed : Kids remember rhymes faster with music than without.
• Color Attraction : Brightly colored toys attract more attention than dull-colored ones.

Simple Hypothesis Statement Examples for Research Paper

In academic settings, crafting a straightforward hypothesis helps anchor a research paper, allowing readers to quickly understand the focal point. Here are concise research hypothesis statements ideal for academic exploration.

• Diet and Cholesterol : A Mediterranean diet lowers cholesterol levels more effectively than a Western diet.
• Urban Development : Rapid urbanization leads to increased air pollution.
• Language Acquisition : Immersion learning accelerates second language acquisition compared to classroom learning.
• Climate Change : Increasing global temperatures directly correlate with rising sea levels.
• Digital Learning : Online education reduces classroom engagement levels.
• Consumer Behavior : Discount offers increase sales during festive seasons.
• Migration Patterns : Economic downturns in a region trigger increased migration.
• Environmental Conservation : Protected wildlife zones reduce species extinction rates.
• Cultural Influence : Exposure to global media diminishes local cultural practices.
• Public Health : Regular public health campaigns reduce the spread of infectious diseases.

Simple Hypothesis Statement Examples for Nursing

In nursing, hypotheses aim to shed light on patient care, health outcomes, and the intricacies of the medical field. These focused statements offer directions for nursing research and practice.

• Post-Operative Recovery : Patients with post-operative physiotherapy recover faster than those without.
• Pain Management : Music therapy reduces the need for pain medication in chronic pain patients.
• Infant Care : Skin-to-skin contact immediately after birth strengthens mother-infant bonding.
• Elderly Health : Regular social interactions decrease the onset of dementia in the elderly.
• Disease Awareness : Regular health check-ups reduce late-stage disease diagnoses.
• Mental Health : Group therapy sessions enhance coping mechanisms for depression patients.
• Patient Satisfaction : Nurse-patient ratios are directly proportional to patient satisfaction rates.
• Medication Adherence : Simplified medication regimens increase adherence in elderly patients.
• Diet and Recovery : High protein diets speed up wound healing in hospitalized patients.
• Sleep and Health : Night-shift workers report higher levels of fatigue than day-shift workers.

Simple Hypothesis Statement Examples in Psychology

Psychology delves deep into the human psyche. Simple pyschology hypothesis in this domain assist in understanding behavioral patterns, cognitive functions, and emotional dynamics. Here are statements reflective of common psychological queries.

• Child Behavior : Children exposed to violent media exhibit more aggressive behaviors.
• Memory and Age : Memory recall decreases with advancing age.
• Group Dynamics : Individuals in larger groups are less likely to exhibit helping behaviors.
• Stress and Performance : Moderate levels of stress enhance performance on cognitive tasks.
• Mood and Perception : Positive moods increase the likelihood of optimistic future expectations.
• Learning Styles : Visual learners retain graphic information better than auditory information.
• Emotions and Decision Making : Intense emotions impair rational decision-making processes.
• Peer Pressure : Adolescents are more likely to engage in risk-taking behaviors under peer influence.
• Personality and Career Choices : Introverts are more drawn to independent job roles than extroverts.
• Dream Patterns : Exposure to traumatic events increases the frequency of nightmares.

Simple Hypothesis Statement Examples for Research

Effective research begins with a precise hypothesis. These straightforward declarations guide the investigative journey, providing clarity in discerning outcomes and assessing implications.

• Technology and Employment : Automation in industries leads to a reduction in manual jobs.
• Marketing Techniques : Influencer marketing garners more engagement than traditional advertising.
• Environmental Initiatives : Implementing green technologies reduces corporate carbon footprints.
• Dietary Habits : Vegan diets result in lower carbon footprints than omnivorous diets.
• Economic Policies : Tax breaks for the middle class stimulate economic growth.
• Educational Systems : Student-led learning methods increase long-term knowledge retention.
• Public Policies : Urban green spaces correlate with reduced crime rates.
• Cultural Shifts : Increased global travel promotes intercultural understanding and tolerance.
• Health Trends : Veganism leads to reduced risks of heart-related diseases.
• Digital Consumption : Increased screen time is linked to declining mental well-being.

Simple vs Complex Hypothesis example

When it comes to scientific research, hypotheses play a pivotal role in guiding investigations. At the core, a hypothesis is a statement about a potential relationship between variables, or an explanation of an occurrence, which is testable. Based on their structural and conceptual nature, hypotheses can be categorized into simple and complex.

A simple hypothesis is a statement that explains the relationship between two variables – one independent variable and one dependent variable. Because it explains the expected relationship in the simplest form, it’s straightforward to test.

Example: Drinking caffeine improves short-term memory.

In this example:

• Independent Variable : Caffeine consumption
• Dependent Variable : Short-term memory

Complex Hypothesis

A complex good hypothesis , in contrast, deals with the relationship between two or more independent variables and two or more dependent variables. This means it’s multidimensional and requires more intricate testing procedures.

Example: Consuming caffeine and sugar together improves short-term memory and reaction time better than consuming either alone.

• Independent Variables : Caffeine consumption and sugar consumption
• Dependent Variables : Short-term memory and reaction time

How do you write a Simple hypothesis statement? – A Step by Step Guide

Step 1: identify your research question.

Every hypothesis stems from a research question. For instance, “Does sunlight affect plant growth?” From this, you can create your hypothesis.

Step 2: Determine the Variables

Every hypothesis has two essential variables:

• Independent Variable : The cause or reason. (Sunlight in our example)
• Dependent Variable : The effect or outcome. (Plant growth in our example)

Step 3: Formulate the Relationship

Specify the expected relationship between the independent and dependent variable. It might be a positive correlation, negative correlation, or no correlation.

Step 4: Keep It Testable

Ensure your hypothesis can be tested empirically. It should be specific enough that experiments or observations can prove or disprove it.

Step 5: Write the Statement

Now, construct your statement. For our example, a potential hypothesis might be: Exposing plants to more sunlight will result in faster growth.

Tips for Writing Simple Hypothesis

• Stay Focused : Stick to one specific relationship between an independent and dependent variable. Avoid including multiple causes or effects to keep it simple.
• Be Clear & Concise : Use clear, straightforward language. Avoid jargon unless it’s necessary for specificity.
• Ensure It’s Testable : A hypothesis is only useful if you can test it. Avoid abstract or overly broad statements.
• Base on Existing Research : While your hypothesis will guide new research, it should be grounded in existing theories or observations.
• Avoid Bias : Ensure your hypothesis doesn’t show any personal beliefs or inclinations. It should be neutral.
• Revisit & Refine : After writing, revisit your hypothesis. Does it still align with your research question? Is there a clearer way to phrase it?
• Stay Open to Changes : Based on the results of your tests or experiments, be prepared to change or adjust your hypothesis.

Remember, a hypothesis is an educated guess. It’s not a definitive explanation, but rather a proposed one, and its primary purpose is to guide your research. Whether your hypothesis gets supported or refuted, the insights you gain are invaluable.

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