experiments with different variables

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Science Fair Project Ideas for Kids, Middle & High School Students ⋅

Ideas for Controlled Variable Science Projects

Science Projects With Three Variables for Kids in Fifth Grade

Many science projects investigate a combination of independent and controlled variables to see what happens as a result - the dependent variable. To get reliable results from your experiments, you change the independent variables carefully and the controlled variables as little as possible; this ensures that only the things you're interested in affect your experimental results.

Does Sugar Dissolve More Quickly in Warm or Cool Water?

Heat a cup of water while allowing another cup of water to remain cool. Dissolve one teaspoon of sugar in each cup of water. The controlled variable would be the number of times and the pressure used to stir the mixture because added motion of the water may or may not dissolve the sugar more quickly whether the water is warm or cool. Record the amount of undissolved sugar in the bottom of the container.

Does a Plant Grow Better in Direct or Indirect Sunlight?

A science project involving plants has controlled variables in the amount of water given to each plant and the amount and kind of soil in which the plant is living. Place one plant in direct sunlight and the other in a shaded area or indoors to conduct the science experiment. Record daily results in the height of the plant.

Will a Baby Bunny Grow Bigger When Fed Rabbit Food or Fresh Vegetables?

Two rabbits, ideally from the same litter, can be used to conduct a classroom experiment. Give each rabbit a different diet: one of only fresh vegetables such as lettuce, carrots and celery; feed the other rabbit pellets from the pet store. The controlled variable in this experiment would be the weight in food each rabbit receives even though the type of food is different. Record the height, weight and length of the two rabbits each week.

Which Will Clean a Penny Faster, Water or Vinegar?

In two glass containers, place one cup of distilled water in one and white vinegar in the other. Carefully drop a dirty penny into each container of liquid and record the changes in the penny's appearance over the course of one week. The controlled variable is in the amount of liquid used to clean each penny.

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Science Project Ideas for Kids: Variables: Independent, Dependent, Controlled
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Variables in Research: Breaking Down the Essentials of Experimental Design

Understanding the role of variables in research is essential for designing and conducting experiments that produce accurate and reliable results. learn about the different types of variables and how they are used in experimental design, with examples of independent and dependent variables.

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9 Great Ways to Teach Variables in Science Experiments

by Katrina | Feb 17, 2024 | Pedagogy , Science | 1 comment

Science is a journey of exploration and discovery, and at the heart of every scientific experiment lies the concept of variables. Variables in science experiments are the building blocks of experimentation, allowing scientists to manipulate and measure different elements to draw meaningful conclusions.

Teaching students about variables is crucial for developing their scientific inquiry skills and fostering a deeper understanding of the scientific method.

In this blog post, we’ll explore the importance of teaching variables in science experiments, delve into the distinctions between independent, dependent, and controlled variables, and provide creative ideas on how to effectively teach these variable types.

So grab a coffee, find a comfy seat, and relax while we explore fun ways to teach variables in science experiments!

The Importance of Teaching Variables in Science Experiments:

Foundation of Scientific Inquiry: Variables form the bedrock of the scientific method. Teaching students about variables helps them grasp the fundamental principles of scientific inquiry, enabling them to formulate hypotheses, design experiments, and draw valid conclusions.

Critical Thinking Skills: Understanding variables cultivates critical thinking skills in students. It encourages them to analyze the relationships between different factors, question assumptions, and think systematically when designing and conducting experiments.

Real-world Application: Variables are not confined to the laboratory; they exist in everyday life. Teaching students about variables equips them with the skills to critically assess and interpret the multitude of factors influencing phenomena in the real world, fostering a scientific mindset beyond the classroom.

In addition to the above, understanding scientific variables is crucial for designing an experiment and collecting valid results because variables are the building blocks of the scientific method.

A well-designed experiment involves the careful manipulation and measurement of variables to test hypotheses and draw meaningful conclusions about the relationships between different factors. Here are several reasons why a clear understanding of scientific variables is essential for the experimental process:

1. Precision and Accuracy: By identifying and defining variables, researchers can design experiments with precision and accuracy. This clarity helps ensure that the measurements and observations made during the experiment are relevant to the research question, reducing the likelihood of errors or misinterpretations.

2. Hypothesis Testing: Variables in science experiments are central to hypothesis formulation and testing. A hypothesis typically involves predicting the relationship between an independent variable (the one manipulated) and a dependent variable (the one measured). Understanding these variables is essential for constructing a hypothesis that can be tested through experimentation.

3. Controlled Experiments: Variables, especially controlled variables, enable researchers to conduct controlled experiments. By keeping certain factors constant (controlled variables) while manipulating others (independent variable), scientists can isolate the impact of the independent variable on the dependent variable. This control is essential for drawing valid conclusions about cause-and-effect relationships.

4. Reproducibility: Clear identification and understanding of variables enhance the reproducibility of experiments. When other researchers attempt to replicate an experiment, a detailed understanding of the variables involved ensures that they can accurately reproduce the conditions and obtain similar results.

5. Data Interpretation: Knowing the variables in science experiments allows for a more accurate interpretation of the collected data. Researchers can attribute changes in the dependent variable to the manipulation of the independent variable and rule out alternative explanations. This is crucial for drawing reliable conclusions from the experimental results.

6. Elimination of Confounding Factors: Without a proper understanding of variables, experiments are susceptible to confounding factors—unintended variables that may influence the results. Through careful consideration of all relevant variables, researchers can minimize the impact of confounding factors and increase the internal validity of their experiments.

7. Optimization of Experimental Design: Understanding variables in science experiments helps researchers optimize the design of their experiments. They can choose the most relevant and influential variables to manipulate and measure, ensuring that the experiment is focused on addressing the specific research question.

8. Applicability to Real-world Situations: A thorough understanding of variables enhances the applicability of experimental results to real-world situations. It allows researchers to draw connections between laboratory findings and broader phenomena, contributing to the advancement of scientific knowledge and its practical applications.

The Different Types of Variables in Science Experiments:

There are 3 main types of variables in science experiments; independent, dependent, and controlled variables.

1. Independent Variable:

The independent variable is the factor that is deliberately manipulated or changed in an experiment. The independent variable affects the dependent variable (the one being measured).

Example : In a plant growth experiment, the amount of sunlight the plants receive can be the independent variable. Researchers might expose one group of plants to more sunlight than another group.

2. Dependent Variable:

The dependent variable is the outcome or response that is measured in an experiment. It depends on the changes made to the independent variable.

Example : In the same plant growth experiment, the height of the plants would be the dependent variable. This is what researchers would measure to determine the effect of sunlight on plant growth.

3. Controlled Variable:

Controlled variables, also called constant variables, are the factors in an experiment that are kept constant to ensure that any observed changes in the dependent variable are a result of the manipulation of the independent variable. These are not to be confused with control groups.

In a scientific experiment in chemistry, a control group is a crucial element that serves as a baseline for comparison. The control group is designed to remain unchanged or unaffected by the independent variable, which is the variable being manipulated in the experiment.

The purpose of including a control group is to provide a reference point against which the experimental results can be compared, helping scientists determine whether the observed effects are a result of the independent variable or other external factors.

Example : In the plant growth experiment, factors like soil type, amount of water, type of plant and temperature would be control variables. Keeping these constant ensures that any differences in plant height can be attributed to changes in sunlight.

Science variables in science experiments

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Best resources for reviewing variables in science experiments:

If you’re short on time and would rather buy your resources, then I’ve compiled a list of my favorite resources for teaching and reviewing variables in science experiments below. While there is nothing better than actually doing science experiments, this isn’t feasible every lesson and these resources are great for consolidation of learning:

1. FREE Science Variables Posters : These are perfect as a visual aide in your classroom while also providing lab decorations! Print in A4 or A3 size to make an impact.

2. Variable scenarios worksheet printable : Get your students thinking about variable with these train your pet dragon themed scenarios. Students identify the independent variable, dependent variable and controlled variables in each scenario.

3. Variable Valentines scenarios worksheet printable : Get your students thinking about variables with these cupid Valentine’s Day scenarios. Students identify the independent variable, dependent variable and controlled variables in each scenario.

4. Variable Halloween scenarios worksheet printable : Spook your students with these Halloween themed scenarios. Students identify the independent variable, dependent variable and controlled variables in each scenario.

5. Scientific Method Digital Escape Room : Review all parts of the scientific method with this fun (zero prep) digital escape room!

6. Scientific Method Stations Printable or Sub Lesson : The worst part of being a teacher? Having to still work when you are sick! This science sub lesson plan includes a fully editable lesson plan designed for a substitute teacher to take, including differentiated student worksheets and full teacher answers. This lesson involves learning about all parts of the scientific method, including variables.

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9 teaching strategies for variables in science experiments.

To help engage students in learning about the different types of scientific variables, it is important to include a range of activities and teaching strategies. Here are some suggestions:

1. Hands-on Experiments: Conducting hands-on experiments is one of the most effective ways to teach students about variables. Provide students with the opportunity to design and conduct their experiments, manipulating and measuring variables to observe outcomes.

Easy science experiments you could include might relate to student heart rate (e.g. before and after exercise), type of ball vs height it bounces, amount of sunlight on the growth of a plant, the strength of an electromagnet (copper wire around a nail) vs the number of coils.

Change things up by sometimes having students identify the independent variable, dependent variable and controlled variables before the experiment, or sometimes afterwards.

Consolidate by graphing results and reinforcing that the independent variable goes alone the x-axis while the dependent variable goes on the y-axis.

2. Teacher Demonstrations:

Use demonstrations to illustrate the concepts of independent, dependent, and controlled variables. For instance, use a simple chemical reaction where the amount of reactant (independent variable) influences the amount of product formed (dependent variable), with temperature and pressure controlled.

3. Case Studies:

Introduce case studies that highlight real-world applications of variables in science experiments. Discuss famous experiments or breakthroughs in science where variables played a crucial role. This approach helps students connect theoretical knowledge to practical situations.

4. Imaginary Situations:

Spark student curiosity and test their understanding of the concept of variables in science experiments by providing imaginary situations or contexts for students to apply their knowledge. Some of my favorites to use are this train your pet dragon and Halloween themed variables in science worksheets.

5. Variable Sorting Activities:

Engage students with sorting activities where they categorize different variables in science experiments into independent, dependent, and controlled variables. This hands-on approach encourages active learning and reinforces their understanding of variable types.

6. Visual Aids:

Utilize visual aids such as charts, graphs, and diagrams to visually represent the relationships between variables. Visualizations can make abstract concepts more tangible and aid in the comprehension of complex ideas.

7. Technology Integration:

Leverage technology to enhance variable teaching. Virtual simulations and interactive apps can provide a dynamic platform for students to manipulate variables in a controlled environment, fostering a deeper understanding of the cause-and-effect relationships.

Websites such as Phet are a great tool to use to model these types of scientific experiments and to identify and manipulate the different variables

8. Group Discussions:

Encourage group discussions where students can share their insights and experiences related to variables in science experiments. This collaborative approach promotes peer learning and allows students to learn from each other’s perspectives.

9. Digital Escape Rooms:

Reinforce learning by using a fun interactive activity like this scientific method digital escape room.

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Teaching variables in science experiments is an essential component of science education, laying the groundwork for critical thinking, inquiry skills, and a lifelong appreciation for the scientific method.

By emphasizing the distinctions between independent, dependent, and controlled variables and employing creative teaching strategies, educators can inspire students to become curious, analytical, and scientifically literate individuals.

What are your favorite ways to engage students in learning about the different types of variables in science experiments? Comment below!

Note: Always consult your school’s specific safety guidelines and policies, and seek guidance from experienced colleagues or administrators when in doubt about safety protocols.

Teaching variables in science experiments

About the Author

Katrina Harte is a multi-award winning educator from Sydney, Australia who specialises in creating resources that support teachers and engage students.

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Independent and Dependent Variables Examples

The independent and dependent variables are key to any scientific experiment, but how do you tell them apart? Here are the definitions of independent and dependent variables, examples of each type, and tips for telling them apart and graphing them.

Independent Variable

The independent variable is the factor the researcher changes or controls in an experiment. It is called independent because it does not depend on any other variable. The independent variable may be called the “controlled variable” because it is the one that is changed or controlled. This is different from the “ control variable ,” which is variable that is held constant so it won’t influence the outcome of the experiment.

Dependent Variable

The dependent variable is the factor that changes in response to the independent variable. It is the variable that you measure in an experiment. The dependent variable may be called the “responding variable.”

Examples of Independent and Dependent Variables

Here are several examples of independent and dependent variables in experiments:

In a study to determine whether how long a student sleeps affects test scores, the independent variable is the length of time spent sleeping while the dependent variable is the test score.
You want to know which brand of fertilizer is best for your plants. The brand of fertilizer is the independent variable. The health of the plants (height, amount and size of flowers and fruit, color) is the dependent variable.
You want to compare brands of paper towels, to see which holds the most liquid. The independent variable is the brand of paper towel. The dependent variable is the volume of liquid absorbed by the paper towel.
You suspect the amount of television a person watches is related to their age. Age is the independent variable. How many minutes or hours of television a person watches is the dependent variable.
You think rising sea temperatures might affect the amount of algae in the water. The water temperature is the independent variable. The mass of algae is the dependent variable.
In an experiment to determine how far people can see into the infrared part of the spectrum, the wavelength of light is the independent variable and whether the light is observed is the dependent variable.
If you want to know whether caffeine affects your appetite, the presence/absence or amount of caffeine is the independent variable. Appetite is the dependent variable.
You want to know which brand of microwave popcorn pops the best. The brand of popcorn is the independent variable. The number of popped kernels is the dependent variable. Of course, you could also measure the number of unpopped kernels instead.
You want to determine whether a chemical is essential for rat nutrition, so you design an experiment. The presence/absence of the chemical is the independent variable. The health of the rat (whether it lives and reproduces) is the dependent variable. A follow-up experiment might determine how much of the chemical is needed. Here, the amount of chemical is the independent variable and the rat health is the dependent variable.

How to Tell the Independent and Dependent Variable Apart

If you’re having trouble identifying the independent and dependent variable, here are a few ways to tell them apart. First, remember the dependent variable depends on the independent variable. It helps to write out the variables as an if-then or cause-and-effect sentence that shows the independent variable causes an effect on the dependent variable. If you mix up the variables, the sentence won’t make sense. Example : The amount of eat (independent variable) affects how much you weigh (dependent variable).

This makes sense, but if you write the sentence the other way, you can tell it’s incorrect: Example : How much you weigh affects how much you eat. (Well, it could make sense, but you can see it’s an entirely different experiment.) If-then statements also work: Example : If you change the color of light (independent variable), then it affects plant growth (dependent variable). Switching the variables makes no sense: Example : If plant growth rate changes, then it affects the color of light. Sometimes you don’t control either variable, like when you gather data to see if there is a relationship between two factors. This can make identifying the variables a bit trickier, but establishing a logical cause and effect relationship helps: Example : If you increase age (independent variable), then average salary increases (dependent variable). If you switch them, the statement doesn’t make sense: Example : If you increase salary, then age increases.

How to Graph Independent and Dependent Variables

Plot or graph independent and dependent variables using the standard method. The independent variable is the x-axis, while the dependent variable is the y-axis. Remember the acronym DRY MIX to keep the variables straight: D = Dependent variable R = Responding variable/ Y = Graph on the y-axis or vertical axis M = Manipulated variable I = Independent variable X = Graph on the x-axis or horizontal axis

Babbie, Earl R. (2009). The Practice of Social Research (12th ed.) Wadsworth Publishing. ISBN 0-495-59841-0.
di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 978-0-521-29925-1.
Gauch, Hugh G. Jr. (2003). Scientific Method in Practice . Cambridge University Press. ISBN 978-0-521-01708-4.
Popper, Karl R. (2003). Conjectures and Refutations: The Growth of Scientific Knowledge . Routledge. ISBN 0-415-28594-1.

What Is a Variable in Science?

Understanding Variables in a Science Experiment

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Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
B.A., Physics and Mathematics, Hastings College

Variables are an important part of science projects and experiments. What is a variable? Basically, a variable is any factor that can be controlled, changed, or measured in an experiment. Scientific experiments have several types of variables. The independent and dependent variables are the ones usually plotted on a chart or graph, but there are other types of variables you may encounter.

Types of Variables

Independent Variable: The independent variable is the one condition that you change in an experiment. Example: In an experiment measuring the effect of temperature on solubility, the independent variable is temperature.
Dependent Variable: The dependent variable is the variable that you measure or observe. The dependent variable gets its name because it is the factor that is dependent on the state of the independent variable . Example: In the experiment measuring the effect of temperature on solubility, solubility would be the dependent variable.
Controlled Variable: A controlled variable or constant variable is a variable that does not change during an experiment. Example : In the experiment measuring the effect of temperature on solubility, controlled variable could include the source of water used in the experiment, the size and type of containers used to mix chemicals, and the amount of mixing time allowed for each solution.
Extraneous Variables: Extraneous variables are "extra" variables that may influence the outcome of an experiment but aren't taken into account during measurement. Ideally, these variables won't impact the final conclusion drawn by the experiment, but they may introduce error into scientific results. If you are aware of any extraneous variables, you should enter them in your lab notebook . Examples of extraneous variables include accidents, factors you either can't control or can't measure, and factors you consider unimportant. Every experiment has extraneous variables. Example : You are conducting an experiment to see which paper airplane design flies longest. You may consider the color of the paper to be an extraneous variable. You note in your lab book that different colors of papers were used. Ideally, this variable does not affect your outcome.

Using Variables in Science Experiment

In a science experiment , only one variable is changed at a time (the independent variable) to test how this changes the dependent variable. The researcher may measure other factors that either remain constant or change during the course of the experiment but are not believed to affect its outcome. These are controlled variables. Any other factors that might be changed if someone else conducted the experiment but seemed unimportant should also be noted. Also, any accidents that occur should be recorded. These are extraneous variables.

Variables and Attributes

In science, when a variable is studied, its attribute is recorded. A variable is a characteristic, while an attribute is its state. For example, if eye color is the variable, its attribute might be green, brown, or blue. If height is the variable, its attribute might be 5 m, 2.5 cm, or 1.22 km.

Earl R. Babbie. The Practice of Social Research , 12th edition. Wadsworth Publishing, 2009.
Examples of Independent and Dependent Variables
Difference Between Independent and Dependent Variables
The Difference Between Control Group and Experimental Group
Null Hypothesis Examples
Random Error vs. Systematic Error
A to Z Chemistry Dictionary
Scientific Variable
What Is an Experiment? Definition and Design
What Is a Dependent Variable?
Independent Variable Definition and Examples
Scientific Method Vocabulary Terms
Dependent Variable Definition and Examples
Six Steps of the Scientific Method
The Role of a Controlled Variable in an Experiment
What Is the Difference Between a Control Variable and Control Group?
DRY MIX Experiment Variables Acronym

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How to teach controlled variable investigations at 11–14

By Primrose Kitten 2021-06-08T10:48:00+01:00

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Get your younger students confident with different types of variables and conducting well-controlled investigations

A photo of two scientists working in a lab

Source: © Karen Ducey/Getty Images

Controlling variables is key in real-life contexts such as clinical trials. Here, medical lab scientists are working on samples collected in the Novavax phase 3 Covid-19 vaccine trial

There has never been a better time to talk about controlled variable investigations. The recent introduction of a Covid-19 vaccine has put clinical trials in the press and at the forefront of everyone’s minds. When carrying out clinical trials, scientists need to determine the efficacy of new vaccines. A large part of this is by controlling the variables – such as participant age and gender, medical history, other current medications and even where they live.

Teaching independent investigations to 11–14-year-old students will help them become scientifically literate citizens and young scientists with a passion for the subject.

What students need to know

The different types of variables: independent variable (what we’re changing); dependent variable (what we’re measuring/observing); control variables (what we’re controlling).
How to control a variable, the importance of using suitably sized equipment (such as measuring cylinders) and the need to be consistent and accurate in our approach.
An experiment is only valid if the influence of the independent variable on the dependent variable has been isolated by controlling the other variables.

Download this

A wrong report for students to correct from the Education in Chemistry website: rsc.li/LINK

Download this

An investigation on dissolving sugar includes some deliberate mistakes, which students should identify and correct. Download the wrong report worksheet as MS Word or pdf and the answers as MS Word or pdf .

Download all

Ideas for the classroom

This may seem like an odd confession, but I miss coursework. Not the marking bit, obviously, but I miss students doing the coursework. It was their chance to be a real scientist for a short while, and our chance as teachers to fill them with a love of working in a lab.

Some courses, such as the previous Salters chemistry A-level, had students undertaking a week-long independent investigation in the laboratory. This was a joy to plan and supervise with students and it was excellent university preparation for them too. I started preparing students for this as soon as they started at my school.

Getting students to plan their controlled variable investigations takes a bit more time than giving them a ready-made practical. It also requires the teacher to train students in how to plan a practical, as well as high levels of teacher and technician patience. You may end up running a session with several different variations of the same experiment going on – but it is worth it.

Take the investigation into how sugar dissolves. This is a relatively safe practical to do, so having lots of different variations at the same time shouldn’t cause too much of a headache. Start by posing the question ‘How long does it take for sugar to dissolve?’ Ask your students to discuss what we can measure and what we can change. Some students may need some support to get them going. I like to use the students’ own words, and then introduce the appropriate technical vocabulary later.

Asking a class of 11-year-olds to list all the control variables might seem like a tricky concept. But by starting them thinking of everything that could be changed, they are developing their concept of control variables naturally.

I love giving my students the chance to develop their own methodology. One group might measure the time to dissolve or the effect of stirring. Another group might look at how much they can dissolve based on changing the type of sugar. Trust me, the classroom never looks as chaotic as this might sound.

A cartoon of an experiment using a stopwatch to time sugar dissolving in water

Source: Composite image all © Shutterstock

Use a practical such as dissolving sugar to introduce students to different types of variables

Discuss with your students how all the other variables in the ‘We can change…’ column then become the control variables. Ask them to plan how they will control each of these variables. The lower years may just be able to describe this in basic terms, for example ‘we need to keep the amount of sugar the same.’ Help them to improve their planning by modelling more sophisticated explanations such as ‘we will use 5 g of sugar in each experiment, measured on a mass balance.’ As your students grow in their knowledge, they can expand their thinking and give explanations of why controlling variables is important. For example: ‘the temperature of the water should be controlled, because an increase in temperature may affect the rate of the dissolution.’

This can all take a little longer than just giving them an instruction sheet, but they will learn a lot more. I use one lesson to plan, followed by homework for them to write up. I then collect it in the next lesson, check their work for a sensible method, and then allow them to experiment in the third lesson.

Common misconceptions

Students will need to understand the difference between repeatability and reproducibility. Emphasise that always taking care to control variables will lead to reproducible experiments (they can be replicated by a different group giving similar results) and repeatable experiments (when repeated by the same group, the results will be similar). Point out to students who do not take care of controlling their variables that their results will be inaccurate and that no valid conclusion can be drawn.

A photo of high school students in a practical chemistry lesson

Source: © Monkey Business Images/Getty Images

Controlling variables will mean that multiple groups conducting the same experiment should get reproducible and repeatable results

Students will commonly equate repeating measurements multiple times with the idea of a ‘fair test’. Explicitly discuss how fair test is a shorthand for ‘a well-controlled investigation’, while repeating measurements allows us to identify anomalies and minimise random errors in our data.

Formative assessment

While I mourn the passing of coursework, I don’t necessarily miss the marking. However, written practical reports are a useful way of having students show they really understand the differences between the variables, the importance of controls and the need to be explicit in how they are controlled. Think carefully about how many of these you ask them to write. A small number of reports per year that you can give high-quality feedback on will have much more impact than lots of reports you don’t have time to mark properly.

You can also make use of ‘wrong reports’, where a ‘student’ has made some mistakes in their planning or write up. Ask your students to identify the errors and write corrections to the work. An example activity on dissolving sugar is available in the downloads.

Progression to 14–16

Students will have many opportunities to carry out controlled investigations during their next stage of education. Use the terminology of ‘independent’, ‘dependent’ and ‘control’ often, including when you are carrying out demonstrations. This will help them appreciate that these variables aren’t just something they have to contend with in their practical work. The variables are a fundamental part of how science works.

Take-home points

Controlling variables allows us to be more confident in the validity of our conclusions from experiments.
Take care to emphasise the need to be accurate with language. For example, the difference between reproducibility and repeatability, and the use of the phrase ‘well-controlled investigation’ rather than ‘fair test’.
Give your students some freedom in making choices on how they carry out practical investigations.
Well-controlled practical activities will allow students to measure and observe data that supports the concepts they will study later in their school career.
Applying scientific method
Asking scientific questions
Designing experiments
Developing teaching practice
Investigation
Practical skills and safety
Professional development

A hand pouring a spoon of sugar into a beaker of water

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Part of Biology Working scientifically

A variable is a factor that can be changed in an experiment.
Identifying control variables, independent and dependent variables is important in making experiments fair.
Knowing about variables can help you make scientific predictions and test them.

True or false?

When changing the height from which a ball is dropped to see how high it bounces, the height from which it is dropped can be a variable.

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Video - a series of experiments.

Watch this video of a number of experiments being carried out.

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After watching the video, make a note of what is being changed (the independent variable), measured (the dependent variable) and kept the same (the control variables)

Video Transcript Video Transcript

Presenter 2: We want to understand some of the different types of variables. To do this, we are going to run through an experiment.

Presenter 1: For example, what will happen if I put a beaker on top of a candle?

Presenter 2: To investigate this, you need to think about the variables involved to obtain valid results.

Presenter 1: Variables are things that you can change or measure in an experiment.

Presenter 2: The independent variable is the one you change. The dependent variable is what you measure afterwards.

Presenter 1: In this experiment, we need to measure the time it takes to candle to go out. That is our dependent variable.

Students: Are we ready? And…out. OK, 11…

Presenter 2: So, let's change the volume of the beaker and that is our independent variable.

Student 2: Ready to start the time? And… now. The bigger the beaker, the more oxygen can fit in which means it'll last longer,which is proven here.

Presenter 1: To make this a valid experiment, we need to make sure we only change one variable. Other variables are kept the same or controlled. The control variable is the candle, so we have to use identical candles.

Presenter 2: That means a brand new candle each time. We also need to seal the gap between the beaker and the mat to stop air escaping or entering. This helps us ensure only one variable is changing in this experiment.

Presenter 1: And this means our experiment is valid.

Presenter 2: So now, not only can we see the difference between independent and dependent variables, but we can also consider the control variable to ensure a valid experiment.

Planning an experiment

Scientists ask questions to find out more about the world, like ‘how can we get more energy from the sun?’ and ‘how can we cure diseases?’. To answer these questions scientists do experiments. During experiments, factors that can change are called variables .

A variable is anything that can change and be measured. Two important types of variables are:

Independent variables – the variable that is being changed during the experiment

Dependent variables – the variable being tested or measured during the experiment

In an experiment, the effect of changing just one variable on another is tested - testing how the independent variable affects the dependent variable. For this reason, other variables must be controlled so that they don't affect the independent variable. These variables are control variables close control variable A variable which must be kept the same so that the result of the experiment is not affected. .

Making predictions

A diagram of three head outlines on a chalkboard. First head has a question mark in. Second head has a lightbulb in. Third head has an exclamation point in.

Ideas for Controlled-Variable Science Projects

Understanding the definition and different types of variables is vital to properly conducting any science experiment. An independent variable is what you intentionally change in order to measure the effect of the dependent variable.To measure both of these, you must also have controlled variables: factors that remain consistent throughout every part of the experiment. Controlled variables ensure that the different elements of an experiment are similar enough that you know what is being changed or tested.

Direct vs. Indirect Sunlight

This experiment checks whether a particular kind of plant prefers direct or indirect sunlight. Get two specimens of the same small plant that can easily be checked on and moved. Put one in an area that receives lots of direct sunlight. Put the other in an area that gets only indirect sunlight. Water both plants the same measured amount and see which grows better. This experiment demonstrates how sunlight affects different kinds of plants, reinforcing the differing needs of different kinds of plant life. The controlled variables in this experiment are the type of plant used and the amount of water received. With different kinds of plants, or inconsistent watering, how well each plant grew might not be a factor of sunlight alone.

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Experiment with what rolls faster by covering one of two planks with a smooth lining like shelf paper and thge other with a rough lining like carpet or astroturf. Place the planks at an angle and roll a tennis or golf ball down each plank simultaneously. Observe which ball reaches the ground first. In most cases, the ball will move fastest on the smooth surface, demonstrating the effect of friction on an object's acceleration. In this experiment, the controlled variable is the angle of the board and the type of ball you roll.

Does Sugar Dissolve Better in Hot Water?

Fill two identical containers with two cups of water each -- one hot and one cold. Add a teaspoon of sugar to each and stir the mixture the same number of times in each container. Use a stopwatch to record how long it takes for a teaspoon of sugar to dissolve in each. In most cases, the sugar will dissolve in the warm water faster, demonstrating that warm mediums -- in which the molecules are moving faster -- dissolve a solid faster than cold mediums. The ratios of water to sugar and the amount of stirring are both controlled variables in this experiment.

Does Water or Vinegar Clean a Penny Better?

Take two dirty pennies and place them in identical shallow containers that can hold liquid. Petri dishes are perfect for this, but a shallow bowl or empty yogurt cup would also work. Cover the penny in one container with 1/8 cup of water, and the other with 1/8 cup of vinegar. After a week, remove the pennies and see which has been cleaned more. The result will usually be that the vinegar cleans the pennies better, demonstrating that a lower-pH solution is better at cleaning discoloration due to oxidation. The volume of liquid and the material of the penny are both controlled variables in this experiment. This experiment is especially good for teaching the concept of a controlled variable if you include a third variable -- how dirty the pennies are.

Discovery Education: Investigation -- Design Experiment
ScienceProjectIdeasForKids.com: Variables: Independent, Dependent, Controlled
ScienceBuddies: From Dull to Dazzling

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Independent Variables

Experiment Controls

Scientific Control

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Identifying Variables

Three types of tomatoes (MOs810, Wikimedia Commons)

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Learn how scientists define independent, dependent and controlled variables in experimental inquiry.

As was mentioned in the Asking Testable Questions backgrounder, testable questions define the variables. In other words, what is being changed and what is to be kept constant, in an experimental inquiry.

What are variables in an experimental inquiry?

Scientists often use experimental inquiries to observe cause and effect relationships. In order to do so, scientists aim to make one change (the cause or independent variable ) in order to determine if the variable is causing what is observed (the effect or dependent variable ).

An experimental inquiry typically has three main types of variables: an independent variable, a dependent variable and controlled variables. We will look at each of these three types of variables and how they are related to experimental inquiries involving plants.

Independent Variables

The independent variable, also known as the experimental treatment , is the difference or change in the experimental conditions that is chosen by the scientist (the cause). To ensure a fair test , a good experimental inquiry only has one independent variable and that variable should be something that can be measured quantitatively. For example, experimental inquiries about plants may include such independent variables as:

Volume of water given to plants
Nitrogen or phosphorus concentration in soil
Duration, intensity or wavelength of light plants are exposed to
Concentration or type of fertilizer

Dependent Variables

When a scientist chooses an independent variable (the cause), that person anticipates a certain response (the effect). This response is known as the dependent variable. The dependent variable should be something that is observable and measurable. Like the independent variable, an experimental inquiry should only have one dependent variable. For example, experimental inquiries about plants may include such dependent variables as:

Days to germination
Surface area of leaves
Days to flowering or fruiting
Dry mass (amount of plant material after all water has been removed)

Testable Question

How does the volume of water affect the number of days it takes for a tomato plant to flower?

Shown is a colour illustration explaining the relationship between an independent and a dependent variable.

On the left is a blue oval with the word "Cause" inside it. This is labelled "Independent Variable" at the top, and "E.g., volume of water" below. On the right is a green rectangle with the word "Effect" inside. This is labelled "Dependent Variable" at the top, and "E.g., days to flowering" below. A red arrow points from cause on the left to the effect on the right.

Controlled Variables

In order for a scientist to ensure that only the independent variable is affecting the dependent variable, all the other factors acting upon the test situation (or test subjects) must be kept constant. The factors that must be kept the same are called the controlled variables , or constant variables. In a given inquiry, there may be one or more variables that will need to be kept constant. For example, for an experimental inquiry in which you are interested in how the volume of water (independent variable) affects the days to flowering (dependent variable), you would want to keep constant:

The type of seeds
The type of soil
The light source
The humidity in the room
The type of container (e.g., plastic pots vs. clay pots)
The Temperature

Shown is a colour photograph of tomato plants in a greenhouse.

Rows of tomato plants on both sides of the photograph stretch into the distance. Light comes in through a translucent ceiling. The plants are thick with green leaves. Tomato fruit is visible at the bottom of each plant. Most of the fruit is red and some is green.

A failure to control variables other than the independent variable will mean that you will not know which factor is actually causing the effects you see. In the example above, if some of the plants were sitting closer to the window than others, the differential exposure to light could be affecting the number of days to flowering, rather than the volume of water.

For more about designing experiments, see: Setting Up a Fair Test

What are the variables in Tomatosphere™?

In the Seed Investigation, students investigate the germination rates of tomato seeds that have been to space (or exposed to space-like conditions) with seeds that have remained on Earth.

The testable question in the Seed Investigation is:

HOW DOES EXPOSURE TO THE SPACE ENVIRONMENT OR SPACE-LIKE CONDITIONS AFFECT THE GERMINATION RATE OF TOMATO SEEDS?

Independent variable: type of seeds used - Earth seeds versus space seeds (sometimes seeds are treated to space-like conditions in years when seeds do not go to space)

Dependent variable: number of seeds that germinate

Guided Practice

Have students read the following questions and determine the independent, dependent and potential controlled variables.

How does the duration of light exposure affect the surface area of tomato plant leaves?
How does the concentration of nitrogen fertilizer affect the days to flowering of tomato plants?
How does the volume of water (mL) affect the number of days to germination of tomato plants?

In their own words, have students define the terms “Independent variable,” “Dependent variable,” and “Controlled variable.”

Have students brainstorm the variables that should be controlled in the Seed Investigation (e.g., quantity of water, type of soil, type of planting container, temperature, etc.).

Have the students think about the Seed Investigation and brainstorm variables that may not be controllable (e.g., giving plants different amounts of water, some plants being closer to a heat vent than others, using different types of soil, etc.).

Independent variable: duration of light (hours) Dependent variable: surface area of plant leaves (Overall? Largest leaf? All leaves?) Controlled variable(s): quantity of water, type of soil, depth of seeds, source of light, concentration/type of fertilizer (if any); temperature of the room, etc.
Independent variable: Concentration of nitrogen fertilizer Dependent variable: days to flowering (when first flower on plants open) Controlled variable(s): Same type of seeds, same quantity of water, same type of soil, same source of light, same duration of light, etc.
Independent variable: Volume of water in ml (per day) Dependent variable: days to germination (when first seed germinates) Controlled variable(s): Single type of seeds, same type of soil, same volume of soil, same type of pots, same source of light, same duration of light, temperature of the room, same time of day for watering, etc.

What are variables? How to use them in your science projects This page from Science Buddies explains different sorts of variables and how to use them to answer sample questions.

Controlled Variables This article by Explorable covers variables, control groups, and the value of consistency.

What are Independent and Dependent Variables? (2019) This article by ThoughtCo explains how to tell the difference between independent and dependent variables, and how to plot variables on a graph.

Identifying and Controlling Variables in Scientific Investigations (2015) This video (3:16 min.) from SciExperiment Basics explains how to identify and control variables in a scientific inquiry.

Types of Variables in Science Experiments

Student performing science experiment with variables

DESCRIPTION Student performing science experiment with variables
SOURCE wera Rodsawang / Moment / getty

The world is full of variables. Science experiments study these different types of variables to find cause and effect relationships. Explore different variables you can expect in your experiments.

Different Types of Variables in Science

As a budding scientist, you want to learn about the world around you. To do that, it is important to explore cause and effect relationships. You even try to predict what will happen through your hypothesis. To test your hypothesis , you need an experiment with a variable.

Variables are the factors, traits, and conditions you can modify and measure. You’ll find different variables in all types of subjects. But, the most common variables found in a science experiment include dependent, independent , and controlled. Check out what each is through examples.

Independent Variable

In an experiment, you need some type of control. Being able to modify a variable is important to study the effects. The variable you control is called your independent variable . Speaking of cause and effect, the independent variable is your cause.

This variable doesn’t rely on any other variables. It is like an adult in that it is free from outside control of the other variables. Examples of independent variables include:

In an experiment to see what brand of diapers hold the most liquid, the independent variable is the brand.
In an experiment studying plant growth in different types of soil, the independent variable is the soil.

Dependent Variables

The dependent variable is your effect. When it comes to an experiment, dependent variables are what you change or measure. It is dependent on your other variables. For example:

In the diaper experiment, the dependent variable might be how much liquid you add to the diapers to see their liquid capacity.
In the plant experiment, the dependent variable would be the growth of the plant. It is going to change depending on how you change the independent variable (soil) or amount of light.

Control Variables

When doing a science experiment, some variables need to remain constant. These are your control variables . By keeping a variable constant, you ensure your results remain accurate. If you have an experiment without a control, then you can’t be completely sure of the cause and effect. To help you understand this concept, look at our examples.

The control variable in the diaper experiment could be the size of the diaper you use. When testing how much water the different brands can hold, you’ll want to use all the same size diapers. Varying the size of the diaper could skew your results.
In your plant experiment, the temperature is a control variable. When testing the growth in soil, make sure to keep all the plants at a consistent temperature. Without a constant temperature, you wouldn’t be sure if it was the temperature or soil making the plant grow better.

Other Types of Variables

While the big three are typically what you think about when it comes to an experiment, they are not the only variables. However, the other variables that can affect a scientific experiment are a bit harder to explain.

Intervening Variables

When it comes to intervening variables , they’re hard to define because they aren’t as straightforward as dependent, independent, and controlled variables. These variables are abstract correlations between your dependent and independent variables you can’t observe in research. For example:

In an experiment, you find a link between having a low income and having higher heart disease rates. However, being poor doesn’t cause heart disease. Instead, an intervening variable, such as not being able to get preventative screenings or having less access to healthy foods, could be the cause.

Extraneous Variables

There are some variables you aren’t going to look at in your study called the extraneous variables . They aren’t the independent variables, but they are uncontrolled variables that might cause unintended changes to your results.

If you are studying the growth of plants in a particular soil, you need to take into account the water you add or fertilizer used in the soil or other variables that could affect the growth.

Studying Different Types of Variables

When it comes to your science experiment, there are a lot of variables to think about. These include not only the variables you’re studying, but also the ones you aren’t. Dive more into fun science topics by looking at genetic engineering and genotypes .

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Knowledge Base

Methodology

Guide to Experimental Design | Overview, Steps, & Examples

Guide to Experimental Design | Overview, 5 steps & Examples

Published on December 3, 2019 by Rebecca Bevans . Revised on June 21, 2023.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design create a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying.

There are five key steps in designing an experiment:

Consider your variables and how they are related
Write a specific, testable hypothesis
Design experimental treatments to manipulate your independent variable
Assign subjects to groups, either between-subjects or within-subjects
Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any extraneous variables that might influence your results. If random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead. This minimizes several types of research bias, particularly sampling bias , survivorship bias , and attrition bias as time passes.

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, other interesting articles, frequently asked questions about experiments.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Research question	Independent variable	Dependent variable
Phone use and sleep	Minutes of phone use before sleep	Hours of sleep per night
Temperature and soil respiration	Air temperature just above the soil surface	CO2 respired from soil

Then you need to think about possible extraneous and confounding variables and consider how you might control them in your experiment.

	Extraneous variable	How to control
Phone use and sleep	in sleep patterns among individuals.	measure the average difference between sleep with phone use and sleep without phone use rather than the average amount of sleep per treatment group.
Temperature and soil respiration	also affects respiration, and moisture can decrease with increasing temperature.	monitor soil moisture and add water to make sure that soil moisture is consistent across all treatment plots.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Diagram of the relationship between variables in a sleep experiment

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

	Null hypothesis (H )	Alternate hypothesis (H )
Phone use and sleep	Phone use before sleep does not correlate with the amount of sleep a person gets.	Increasing phone use before sleep leads to a decrease in sleep.
Temperature and soil respiration	Air temperature does not correlate with soil respiration.	Increased air temperature leads to increased soil respiration.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

Systematically and precisely manipulate the independent variable(s).
Precisely measure the dependent variable(s).
Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalized and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

just slightly above the natural range for your study region.
over a wider range of temperatures to mimic future warming.
over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

A completely randomized design vs a randomized block design .
A between-subjects design vs a within-subjects design .

Randomization

An experiment can be completely randomized or randomized within blocks (aka strata):

In a completely randomized design , every subject is assigned to a treatment group at random.
In a randomized block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

	Completely randomized design	Randomized block design
Phone use and sleep	Subjects are all randomly assigned a level of phone use using a random number generator.	Subjects are first grouped by age, and then phone use treatments are randomly assigned within these groups.
Temperature and soil respiration	Warming treatments are assigned to soil plots at random by using a number generator to generate map coordinates within the study area.	Soils are first grouped by average rainfall, and then treatment plots are randomly assigned within these groups.

Sometimes randomization isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs. within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomizing or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

	Between-subjects (independent measures) design	Within-subjects (repeated measures) design
Phone use and sleep	Subjects are randomly assigned a level of phone use (none, low, or high) and follow that level of phone use throughout the experiment.	Subjects are assigned consecutively to zero, low, and high levels of phone use throughout the experiment, and the order in which they follow these treatments is randomized.
Temperature and soil respiration	Warming treatments are assigned to soil plots at random and the soils are kept at this temperature throughout the experiment.	Every plot receives each warming treatment (1, 3, 5, 8, and 10C above ambient temperatures) consecutively over the course of the experiment, and the order in which they receive these treatments is randomized.

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Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimize research bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalized to turn them into measurable observations.

Ask participants to record what time they go to sleep and get up each day.
Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Student’s t -distribution
Normal distribution
Null and Alternative Hypotheses
Chi square tests
Confidence interval
Cluster sampling
Stratified sampling
Data cleansing
Reproducibility vs Replicability
Peer review
Likert scale

Research bias

Implicit bias
Framing effect
Cognitive bias
Placebo effect
Hawthorne effect
Hindsight bias
Affect heuristic

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

A testable hypothesis
At least one independent variable that can be precisely manipulated
At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

How you will manipulate the variable(s)
How you will control for any potential confounding variables
How many subjects or samples will be included in the study
How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

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Experimental Design - Independent, Dependent, and Controlled Variables

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Scientific experiments are meant to show cause and effect of a phenomena (relationships in nature). The “ variables ” are any factor, trait, or condition that can be changed in the experiment and that can have an effect on the outcome of the experiment.

An experiment can have three kinds of variables: i ndependent, dependent, and controlled .

The independent variable is one single factor that is changed by the scientist followed by observation to watch for changes. It is important that there is just one independent variable, so that results are not confusing.
The dependent variable is the factor that changes as a result of the change to the independent variable.
The controlled variables (or constant variables) are factors that the scientist wants to remain constant if the experiment is to show accurate results. To be able to measure results, each of the variables must be able to be measured.

For example, let’s design an experiment with two plants sitting in the sun side by side. The controlled variables (or constants) are that at the beginning of the experiment, the plants are the same size, get the same amount of sunlight, experience the same ambient temperature and are in the same amount and consistency of soil (the weight of the soil and container should be measured before the plants are added). The independent variable is that one plant is getting watered (1 cup of water) every day and one plant is getting watered (1 cup of water) once a week. The dependent variables are the changes in the two plants that the scientist observes over time.

Experimental Design - Independent, Dependent, and Controlled Variables

Can you describe the dependent variable that may result from this experiment? After four weeks, the dependent variable may be that one plant is taller, heavier and more developed than the other. These results can be recorded and graphed by measuring and comparing both plants’ height, weight (removing the weight of the soil and container recorded beforehand) and a comparison of observable foliage.

Using What You Learned: Design another experiment using the two plants, but change the independent variable. Can you describe the dependent variable that may result from this new experiment?

Think of another simple experiment and name the independent, dependent, and controlled variables. Use the graphic organizer included in the PDF below to organize your experiment's variables.

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Types of Variables – A Comprehensive Guide

Published by Carmen Troy at August 14th, 2021 , Revised On October 26, 2023

A variable is any qualitative or quantitative characteristic that can change and have more than one value, such as age, height, weight, gender, etc.

Before conducting research, it’s essential to know what needs to be measured or analysed and choose a suitable statistical test to present your study’s findings.

In most cases, you can do it by identifying the key issues/variables related to your research’s main topic.

Example: If you want to test whether the hybridisation of plants harms the health of people. You can use the key variables like agricultural techniques, type of soil, environmental factors, types of pesticides used, the process of hybridisation, type of yield obtained after hybridisation, type of yield without hybridisation, etc.

Variables are broadly categorised into:

Independent variables
Dependent variable
Control variable

Independent Vs. Dependent Vs. Control Variable

Type of variable

Definition

Example

Independent Variable (Stimulus)

It is the variable that influences other variables.

Dependent variable (Response)

The dependent variable is the outcome of the influence of the independent variable.

You want to identify “How refined carbohydrates affect the health of human beings?”

: refined carbohydrates

: the health of human beings

You can manipulate the consumption of refined carbs in your human participants and measure how those levels of consuming processed carbohydrates influence human health.

Control Variables

Control variables are variables that are not changed and kept constant throughout the experiment.

The research includes finding ways:

To change the independent variables.
To prevent the controlled variables from changing.
To measure the dependent variables.

Note: The term dependent and independent is not applicable in correlational research as this is not a controlled experiment. A researcher doesn’t have control over the variables. The association and between two or more variables are measured. If one variable affects another one, then it’s called the predictor variable and outcome variable.

Example: Correlation between investment (predictor variable) and profit (outcome variable)

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Types of Variables Based on the Types of Data

A data is referred to as the information and statistics gathered for analysis of a research topic. Data is broadly divided into two categories, such as:

Quantitative/Numerical data is associated with the aspects of measurement, quantity, and extent.

Categorial data is associated with groupings.

A qualitative variable consists of qualitative data, and a quantitative variable consists of a quantitative variable.

Quantitative Variable

The quantitative variable is associated with measurement, quantity, and extent, like how many . It follows the statistical, mathematical, and computational techniques in numerical data such as percentages and statistics. The research is conducted on a large group of population.

Example: Find out the weight of students of the fifth standard studying in government schools.

The quantitative variable can be further categorised into continuous and discrete.

Type of variable

Definition

Example

Continuous Variable

A continuous variable is a quantitative variable that can take a value between two specific values.

Discrete Variable

A discrete variable is a quantitative variable whose attributes are separated from each other.

Literacy rate, gender, and nationality.

Scale: Nominal and ordinal.

Categorial Variable

The categorical variable includes measurements that vary in categories such as names but not in terms of rank or degree. It means one level of a categorical variable cannot be considered better or greater than another level.

Example: Gender, brands, colors, zip codes

The categorical variable is further categorised into three types:

Type of variable	Definition	Example
Dichotomous (Binary) Variable	This is the categorical variable with two possible results (Yes/No)	Alcoholic (Yes/No)
Nominal Variable	Nominal Variable can take the value that is not organised in terms of groups, degree, or rank.
Ordinal Variable	Ordinal Variable can take the value that can be logically ordered or ranked.

Note: Sometimes, an ordinal variable also acts as a quantitative variable. Ordinal data has an order, but the intervals between scale points may be uneven.

Example: Numbers on a rating scale represent the reviews’ rank or range from below average to above average. However, it also represents a quantitative variable showing how many stars and how much rating is given.

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Other Types of Variables

It’s important to understand the difference between dependent and independent variables and know whether they are quantitative or categorical to choose the appropriate statistical test.

There are many other types of variables to help you differentiate and understand them.

Also, read a comprehensive guide written about inductive and deductive reasoning .

Type of variable

Definition

Example

Confounding variables

The confounding variable is a hidden variable that produces an association between two unrelated variables because the hidden variable affects both of them.

There is an association between water consumption and cold drink sales.

The confounding variable could be the and compels people to drink a lot of water and a cold drink to reduce heat and thirst caused due to the heat.

Latent Variable

These are the variables that cannot be observed or measured directly.

Self-confidence and motivation cannot be measured directly. Still, they can be interpreted through other variables such as habits, achievements, perception, and lifestyle.

Composite variables

A composite variable is a combination of multiple variables. It is used to measure multidimensional aspects that are difficult to observe.

Entertainment
Online education
Database management, storage, and retrieval

Frequently Asked Questions

What are the 10 types of variables in research.

The 10 types of variables in research are:

Independent
Confounding
Categorical
Extraneous.

What is an independent variable?

An independent variable, often termed the predictor or explanatory variable, is the variable manipulated or categorized in an experiment to observe its effect on another variable, called the dependent variable. It’s the presumed cause in a cause-and-effect relationship, determining if changes in it produce changes in the observed outcome.

What is a variable?

In research, a variable is any attribute, quantity, or characteristic that can be measured or counted. It can take on various values, making it “variable.” Variables can be classified as independent (manipulated), dependent (observed outcome), or control (kept constant). They form the foundation for hypotheses, observations, and data analysis in studies.

What is a dependent variable?

A dependent variable is the outcome or response being studied in an experiment or investigation. It’s what researchers measure to determine the effect of changes in the independent variable. In a cause-and-effect relationship, the dependent variable is presumed to be influenced or caused by the independent variable.

What is a variable in programming?

In programming, a variable is a symbolic name for a storage location that holds data or values. It allows data storage and retrieval for computational operations. Variables have types, like integer or string, determining the nature of data they can hold. They’re fundamental in manipulating and processing information in software.

What is a control variable?

A control variable in research is a factor that’s kept constant to ensure that it doesn’t influence the outcome. By controlling these variables, researchers can isolate the effects of the independent variable on the dependent variable, ensuring that other factors don’t skew the results or introduce bias into the experiment.

What is a controlled variable in science?

In science, a controlled variable is a factor that remains constant throughout an experiment. It ensures that any observed changes in the dependent variable are solely due to the independent variable, not other factors. By keeping controlled variables consistent, researchers can maintain experiment validity and accurately assess cause-and-effect relationships.

How many independent variables should an investigation have?

Ideally, an investigation should have one independent variable to clearly establish cause-and-effect relationships. Manipulating multiple independent variables simultaneously can complicate data interpretation.

However, in advanced research, experiments with multiple independent variables (factorial designs) are used, but they require careful planning to understand interactions between variables.

Dependent & Independent Variables in Science Experiments

by Chloe Campbell Leave a Comment

Understanding how variables in science experiments work is an important skill for our students to understand. We do a lot of science experiments in my classroom, and knowing how different factors can change the outcome of a scientific experiment is always something I want them to be able to discover and explain. It’s also great practice for the scientific method. Here are some of the best ways to teach dependent and independent variables in your science classroom.

VARIABLES IN SCIENCE EXPERIMENTS: WHAT ARE THEY?

Here are definitions you can use with your students, using a plant growth experiment as a base:

Example: If you are testing how different amounts of water affect plant growth, the amount of water is the independent variable because it’s what you change in your experiment.
Example: In the plant experiment, the growth of the plant is the dependent variable because it’s what you measure to see how much the plant has grown based on the different amounts of water.

My Independent and Dependent Variables Resource has a foldable, interactive vocabulary activity that helps students understand the concept of variables. In the resource, students also define what control variables are.

It’s important for our students to know the variable that we are changing and the variables that occur because of that one change. It’s also so important to make sure the kids understand how important changing only one thing is. We need to know what caused the outcome of the experiment, and that’s difficult if we change different variables.

Independent, Dependent, and Control Variables

DESIGNING EXPERIMENTS

Once students understand what variables are, we need to help them put this new vocabulary into action. That’s where experiments come in! I like to start with a premade experiment that guide students through how variables work in a real-world context. An easy experiment that I like to use with my students is W hat Will Make Ice Melt the Fastest? . Students work with three different materials that we have on hand in class, and they predict which substance will make ice melt the fastest. I like to use sand, water, salt, sugar, or anything similar. I also make sure students know we need a control group to see what happens when no substance is applied to the ice.

FOCUS ON THE VARIABLES

Students can sometimes get lost in the steps of an experiment and forget what brought the results about. For this reason, I make sure that my students can communicate to each other what the variables were and, more importantly, why each variable exists. For example, in the plant growth experiment, the goal is for my students to be able to explain that:

the independent variable is the amount of water we’re using, because we are changing the amount on purpose;
the dependent variable is the plant’s growth, because that will change based on the water we give it;
the controlled variables are anything we don’t intend to change, which in this case could be the type of soil used, the type of plant used, the amount of light each plant gets, the type of liquid (we always use the same tap water), and so on.

To keep the focus even stronger, the students know that their exit ticket for the class will be for them to explain what an independent, dependent, and controlled variable is. You can have students define in it general, or you can have them provide examples based on the results of the experiment.

ANALYZE THE DATA

Once my students have correctly identified the different types of variables in an experiment, we analyze the data we collected. I want them to understand, and then be able to explain to someone else, how the independent variable affects the dependent variable. For example, in my What Will Make Ice Melt the Fastest? lab, students conclude that the salt melted the ice fastest. The constant variables were anything we didn’t change, such as how long we timed them melting and the temperature of the room. The final outcome of an experiment is important, and knowing the why behind the outcome is important too.

Understanding these variables helps students design good experiments and understand the results better when they go off and create their own scientific investigations. When our students know what we are changing (independent variable) and what we are measuring (dependent variable), they can make better observations and conclusions. Being able to analyze the results of an experiment is a great critical thinking developer, and students pick up scientific inquiry skills they can use throughout the year.

You can grab this entire lesson with everything made for you by clicking the picture below.

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The Different Types Of Variables Used In Research And Statistics

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Types Of Variables

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Scientists and statisticians conduct experiments on a regular basis. Scientists use these experiments to identify cause and effect, while Statisticians use variables to represent the unknown or varied data in their experiments.

Determining which variables to use is vital to the experiment. Also, choosing the right variables will lead to clearer analyses and more accurate results.

What Is a Variable?

A variable is something you can control, manipulate, or measure when conducting research or experiments. They are characteristics, numbers, or quantities and can represent specific items, people, places, or an idea. The variables may be referred to as data items.

The variables in an experiment will vary depending on the desired outcome. All scientific experiments and statistical studies will analyze a variable.

They are referred to as variables because the values can vary. A variable’s value can change within a single experiment. Whether there is a change between the groups being studied or the value changes over time, it may not necessarily be a constant.

Designing Experiments

As noted, all scientific experiments and statistical studies will control, manipulate, or measure a variable. In fact, the experiments are usually designed to determine the effect one variable has on another variable, cause, and effect.

When designing experiments, it is extremely important to choose the right variables. Choosing incorrectly can skew the results and derail the experiment or study completely. Choosing right can help an experiment or study run much more smoothly and produce more accurate results.

It is not just the specific variable within the experiment that needs to be determined, but the variable type as well. Knowing the variable type will allow you to interpret the results of the experiment or study.

It should be noted, though, that categorizing variables is a little subjective. Scientists and statisticians have some wiggle room when they categorize their experiment variables.

Generally, you will need to know what data the variable represents and what part of the experiment the variable represents in order to determine the variable type.

Independent, Dependent, and Control Variables

Typically, there will be an independent variable, dependent variable, and control variable in every experiment or study conducted.

Independent variables. Independent variables are the variables in your experiment that are being manipulated. They are referred to as independent variables due to the fact that their value is independent of other variables, which means that the other variables cannot change the independent variable.

Dependent variables. Dependent variables are the variables in your experiment that rely on other variables and can be changed or manipulated by the other variables being measured.

Control variables. Control variables are the variables in your experiment that are constant. They do not change over the course of the experiment or study and will have no direct effect on the other variables being measured.

Qualitative Versus Quantitative Variables

Every single variable you include in your experiment will need to be categorized as either a qualitative variable or a quantitative variable.

Qualitative variables. Also referred to as categorical variables, qualitative variables are any variables that hold no numerical value. They are nominal labels. For example, eye color would be a qualitative variable. The data being recorded is not a number but a color.

These variables don’t necessarily measure, but they describe a characteristic of the data set. They can be broken down further as either ordinal variables or nominal variables (see below for definitions).

Quantitative variables. Quantitative variables, or numeric variables, are the variables in your experiment that hold a numerical value. Unsurprisingly, they will represent a measurable quantity and will be recorded as a number.

These variables will measure “how many” or “how much” of the data being collected. These can be broken down further as either continuous variables or discrete variables (see below for definitions).

30 Other Variable Types Used in Experiments

This is by no means a comprehensive list, as the list of all variable types would be difficult to document in one place.

Below are many of the common and some less common variable types used in scientific experiments and statistical studies. Included is a brief overview of what that variable type measures.

Active variable. An active variable is a variable that can be manipulated by those running the experiment.

Antecedent variable. Antecedent variables come before the independent and dependent variables. With “antecedent” meaning “preceding in time or order,” this is not surprising.

Attribute variable. An attribute variable also called a passive variable, is not manipulated during the experiment. It may be a fixed variable or simply a variable that is not manipulated for one experiment but could be for another.

Binary variable. Binary variables only have two values. Typically, this will be represented as a zero or one but can be yes/no or another two-value combination.

Categorical variable. Categorical variables are variables that can be divided into larger buckets or categories. Shoe brands, for instance, could include Nike, Reebok, or Adidas.

Composite variable. This variable type is a bit different from others. A composite variable is made up of two or more other variables. The individual variables that make up the composite variable will be closely related either conceptually or statistically.

Confounding variable. Confounding variables are not good. They can affect both independent and dependent variables and invalidate results. Sometimes referred to as a lurking variable, these variables are considered “extra” and were not accounted for during the designing phase.

Continuous variable. Continuous variables have an infinite number of values between the highest point and lowest point. Distance is a continuous variable.

Covariate variable. A covariate variable can affect the dependent variable in addition to the independent variable. It will not be of interest in the results of the experiment, though.

Criterion variable. This is a statistical variable only. It is another name for the dependent variable.

Dichotomous variable. This is another name for a binary variable. Dichotomous variables will have two values only.

Discrete variable. Discrete variables are the opposite of continuous variables. Where continuous variables have an infinite number of possible values, discrete variables have a finite number.

Endogenous variable. Endogenous variables are dependent on other variables and are used only in statistical studies, in econometrics specifically. The value of these variables is determined by the model.

Exogenous variable. An exogenous variable is the opposite of an endogenous variable. The value of this type of variable is determined outside of the model and will have an impact on other variables within the model.

Explanatory variable. This is a commonly used name for the independent variable or the variable that is being manipulated by those running the experiment.

Grouping variable. A grouping variable is used to sort, or split up, the data set into groups or categories.

Interval variable. Interval variables show the meaningful difference between the two values.

Intervening variable. Intervening variables, or mediator variables, explains the cause, connection, or relationship between two other variables being measured.

Manifest variable. A manifest variable is a variable that can be directly observed or measured within the experiment.

Moderating variable. A moderating variable can affect the relationship between the independent variable and dependent variable. It can either strengthen, diminish, or negate the relationship.

Nominal variable. This is another way of saying categorical value. Nominal values will have two or more categories.

Observed variable. Observed variables are variables that are being measured during the experiment.

Ordinal variable. Ordinal variables are similar to categorical or nominal variables but have a clear ordering of categories. Examples such as High to low and like to dislike would both be ordinal variables.

Polychotomous variable. Polychotomous variables have more than two possible categories or values. These can be either nominal or ordinal.

Ranked variable. Ranked variables are ordinal variables. The researcher may not know the exact value, but they will know the order in which the data points should fall.

Ratio variable. Ratio variables are similar to interval variables but have a clear definition of zero.

Responding variable. Responding variables are the effect or outcome of the experiment. Similar to dependent variables, responding variables will “respond” to changes being made in the experiment.

Scale variable. A scale variable is a variable that has a numeric value that can be ordered with a meaningful metric. It will be the amount or number of something.

Study variable. Often referred to as a research variable, a study variable is any variable used that has some kind of cause and effect relationship.

Test variable. A test variable also referred to as the dependent variable, is a variable that represents the outcome of the experiment.

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Chris Kolmar is a co-founder of Zippia and the editor-in-chief of the Zippia career advice blog. He has hired over 50 people in his career, been hired five times, and wants to help you land your next job. His research has been featured on the New York Times, Thrillist, VOX, The Atlantic, and a host of local news. More recently, he's been quoted on USA Today, BusinessInsider, and CNBC.

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Effect of Milling Variables on Particle Deformation in a Stirred Media Mill

Original Research Article
Published: 26 June 2024

Cite this article

R. G. Hamey 1 ,
A. A. El-Midany 2 &
H. E. El-Shall 1

The milling of the metal powder is necessary to produce a certain size or aspect ratio. To achieve this target, the particles undergo several deformations before their breakage. Thus, to show the effect of grinding conditions on particle deformation, the aluminum powder was milled in a stirred media mill at different settings of the media size, stirrer rotational speed, and milling time. Particle size measurements tracked the particle deformation or breakage. The statistical design of experiments was used to predict particle deformation in stirred media mill in terms of grinding media size and impeller rotational speed. The results showed that the acting stress responsible for particle deformation (strain) depends mainly on the media size with a minor effect on rotational speed except at the smallest ball size with no clear interaction between media size and rotation speed. Particle deformation prevails at short milling times, while at longer grinding times, the breakage prevails. A grinding ball size of 1.5 mm shows the highest particle deformation among other ball sizes.

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Data Availability

The authors confirm that the data supporting the findings of this study are available within the article.

A.D.Booz, Metal Flake Production, US Patent, USP1977124065060, 1976.

M.M. Moshksar and S.M. Zebarjad, Morphology and Size Distribution of Aluminum Powder during Milling Processing, Iran. J. Sci. Technol. , 1999, 23 , p 239–250.

CAS Google Scholar

A. Bor, B. Jargalsaikhan, K. Uranchimeg, J. Lee, and H. Choi, Particle Morphology Control of Metal Powder with Various Experimental Conditions Using Ball Milling, powder Technol. , 2021, 394 , p 181–190.

Article CAS Google Scholar

S. Khorasani, H. Abdizadeh, and S.H. Manesh, Evaluation of Structure and Morphology of Aluminum Powder Particles Milled at Different Conditions, Adv. Powder Technol. , 2014, 25 , p 599–603.

H.S. Kim, B. Madavali, T.J. Eom, C.M. Kim, J.M. Koo, T.H. Lee, and S.J. Hong, Effect of Different Mechanical Milling Processes on Morphology and Microstructural Changes of Nano and Micron Al-Powders, Arch. Metall. Mater. , 2015, 60 , p 1235–1239.

H. Zoz, H. Ren, R. Reichardt, H.U. Benz, A. Nadkarni, and G. Wagner, Ductile metal Flakes Based on [Au], [Ag], [Al], [Cu], [Ti], [Zn] and [Fe] Materials by High Energy Milling (HEM)—Part I, in International Conference on Powder Metallurgy & Particulate Materials, PM2TEC (Metal Powder Industries Federation, Princeton 1999), no. 1, p. 1–107.

S.S. Ibrahim, A.A. El-Midany, and T.R. Boulos, The Effect of Intensive Mechanical Stresses on Phosphate Ores Chemistry, Physicochem. Probl. Miner. Process. J. , 2010, 44 , p 79–92.

R. Gamal and A.A. El-Midany, Enhancing Selective Dissolution of Manganese by Mechanochemical Process for Iron Ore Upgrading, Part. Sci. Technol. , 2024, 42 (2), p 255–262.

P.S. Gilman and J.S. Benjamin, Mechanical Alloying, Annu. Rev. Mater. Sci. , 1983, 13 , p 279–300.

L.P. Sung, M.E. Nadal, M.E. McKnight, E. Marx, and B. Laurenti, Optical Reflectance of Metallic Coatings: Effect of Aluminum Flake Orientation, J. Coat. Technol. , 2002, 74 , p 55–63.

S.H. Hong and B.K. Kim, Effects of Lifter Bars on the Ball Motion and Aluminum Foil Milling in Tumbler Ball Mill, Mater. Lett. , 2002, 57 , p 275–279.

J. Zheng, C.C. Harris, and P. Somasundaran, A Study on Grinding and Energy Input in Stirred Media Mills, Powder Technol. , 1996, 86 , p 171–178.

M.Z. He, Y.M. Wang, and E. Forssberg, Parameter Effects on Wet Ultrafine Grinding of Limestone through Slurry Rheology in a Stirred Media Mill, Powder Technol. , 2006, 161 , p 10–21.

S.E. El-Mofty, A.M. El-Bendary, A.A. El-Midany, and M.K. Abdel-Rahman, Effect of Hydrophobicity on Talc Grinding in Attritor Mill, Theor. Found. Chem. Eng. , 2023, 57 (6), p 1424–1430.

A. Jankovic, Media Stress Intensity Analysis for Vertical Stirred Mills, Miner. Eng. , 2001, 14 , p 1177–1186.

A. Jankovic, Variables Affecting the Fine Grinding of Minerals Using Stirred Mills, Miner. Eng , 2003, 16 , p 337–345.

R.G. Hamey, A.A. El-Midany, and H.E. El-Shall, Novel Methodology for Mill Efficiency Determination Based on Particle Deformation, Energy , 2023, 263 , p 125860.

Article Google Scholar

R.G. Hamey, A.A. El-Midany, and H.E. El-Shall, Is it Possible to Use Breakage Models for Predicting Particle Deformation?, JOM , 2024, 76 (2), p 718–725.

ASM, Powder Metal Technologies and Applications, Materials Park, Ohio, 1998.

C. Frances, C. Laguerie, B. Mazzarotta, and T. Veccia, On the Analysis of Fine Wet Grinding in a Batch Ball Mill, Chem. Eng. J. , 1996, 63 , p 141–147.

C. Alamprese, L. Datei, and Q. Semeraro, Optimization of Processing Parameters of a Ball Mill Refiner for Chocolate, J. Food Eng. , 2007, 83 , p 629–636.

Hamey R.G., Particle Deformation During Stirred Media Milling, PhD thesis, Materials Science and Engineering Dept, University of Florida, Gainesville, USA, 2008.

D.C. Montgomery, Design and Analysis of Experiment , John Wiley and Son Inc, New York, 2004.

Google Scholar

R.G. Hamey, A.A. El-Midany, and H.E. El-Shall, How Reliable the Light Scattering in Sizing the Deformable Particles by Milling?, Part. Sci. Technol. , 2023, 41 (5), p 725–729.

N. Khairy, I.A. El-Magd, S.E. El-Mofty, and A.A. El-Midany, Oil Shale Breakage in a Ball Mill Using Different Media Types, Obogashchenie Rud J. , 2021, 4 , p 14–19. ( in Russian )

N. Khairy, I.A. El-Magd, S.E. El-Mofty, and A.A. El-Midany, Sensitivity of Oil Shale Particle Surface to the Applied Load in Ball Mill, Int. J. Coal Prep. Util. , 2022, 42 (11), p 3235–3248.

A. Kwade, L. Blecher, and J. Schwedes, Motion and Stress Intensity of Grinding Beads in a Stirred Media Mill. Part 2: Stress Intensity and Its Effect on Comminution, Powder Technol. , 1996, 86 , p 69–76.

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Acknowledgment

The authors want to acknowledge the financial support of the Particle Engineering Research Center (PERC) at the University of Florida, the National Science Foundation (NSF) and the Industrial Partners of the PERC for support of this research.

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Hamey, R.G., El-Midany, A.A. & El-Shall, H.E. Effect of Milling Variables on Particle Deformation in a Stirred Media Mill. J. of Materi Eng and Perform (2024). https://doi.org/10.1007/s11665-024-09709-8

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