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• Independent vs. Dependent Variables | Definition & Examples

Independent vs. Dependent Variables | Definition & Examples

Published on February 3, 2022 by Pritha Bhandari . Revised on June 22, 2023.

In research, variables are any characteristics that can take on different values, such as height, age, temperature, or test scores.

Researchers often manipulate or measure independent and dependent variables in studies to test cause-and-effect relationships.

• The independent variable is the cause. Its value is independent of other variables in your study.
• The dependent variable is the effect. Its value depends on changes in the independent variable.

Your independent variable is the temperature of the room. You vary the room temperature by making it cooler for half the participants, and warmer for the other half.

Table of contents

What is an independent variable, types of independent variables, what is a dependent variable, identifying independent vs. dependent variables, independent and dependent variables in research, visualizing independent and dependent variables, other interesting articles, frequently asked questions about independent and dependent variables.

An independent variable is the variable you manipulate or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation).

These terms are especially used in statistics , where you estimate the extent to which an independent variable change can explain or predict changes in the dependent variable.

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There are two main types of independent variables.

• Experimental independent variables can be directly manipulated by researchers.
• Subject variables cannot be manipulated by researchers, but they can be used to group research subjects categorically.

Experimental variables

In experiments, you manipulate independent variables directly to see how they affect your dependent variable. The independent variable is usually applied at different levels to see how the outcomes differ.

You can apply just two levels in order to find out if an independent variable has an effect at all.

You can also apply multiple levels to find out how the independent variable affects the dependent variable.

You have three independent variable levels, and each group gets a different level of treatment.

You randomly assign your patients to one of the three groups:

• A low-dose experimental group
• A high-dose experimental group
• A placebo group (to research a possible placebo effect )

A true experiment requires you to randomly assign different levels of an independent variable to your participants.

Random assignment helps you control participant characteristics, so that they don’t affect your experimental results. This helps you to have confidence that your dependent variable results come solely from the independent variable manipulation.

Subject variables

Subject variables are characteristics that vary across participants, and they can’t be manipulated by researchers. For example, gender identity, ethnicity, race, income, and education are all important subject variables that social researchers treat as independent variables.

It’s not possible to randomly assign these to participants, since these are characteristics of already existing groups. Instead, you can create a research design where you compare the outcomes of groups of participants with characteristics. This is a quasi-experimental design because there’s no random assignment. Note that any research methods that use non-random assignment are at risk for research biases like selection bias and sampling bias .

Your independent variable is a subject variable, namely the gender identity of the participants. You have three groups: men, women and other.

Your dependent variable is the brain activity response to hearing infant cries. You record brain activity with fMRI scans when participants hear infant cries without their awareness.

A dependent variable is the variable that changes as a result of the independent variable manipulation. It’s the outcome you’re interested in measuring, and it “depends” on your independent variable.

In statistics , dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

The dependent variable is what you record after you’ve manipulated the independent variable. You use this measurement data to check whether and to what extent your independent variable influences the dependent variable by conducting statistical analyses.

Based on your findings, you can estimate the degree to which your independent variable variation drives changes in your dependent variable. You can also predict how much your dependent variable will change as a result of variation in the independent variable.

Distinguishing between independent and dependent variables can be tricky when designing a complex study or reading an academic research paper .

A dependent variable from one study can be the independent variable in another study, so it’s important to pay attention to research design .

Here are some tips for identifying each variable type.

Recognizing independent variables

Use this list of questions to check whether you’re dealing with an independent variable:

• Is the variable manipulated, controlled, or used as a subject grouping method by the researcher?
• Does this variable come before the other variable in time?
• Is the researcher trying to understand whether or how this variable affects another variable?

Recognizing dependent variables

Check whether you’re dealing with a dependent variable:

• Is this variable measured as an outcome of the study?
• Is this variable dependent on another variable in the study?
• Does this variable get measured only after other variables are altered?

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Independent and dependent variables are generally used in experimental and quasi-experimental research.

Here are some examples of research questions and corresponding independent and dependent variables.

For experimental data, you analyze your results by generating descriptive statistics and visualizing your findings. Then, you select an appropriate statistical test to test your hypothesis .

The type of test is determined by:

• your variable types
• level of measurement
• number of independent variable levels.

You’ll often use t tests or ANOVAs to analyze your data and answer your research questions.

In quantitative research , it’s good practice to use charts or graphs to visualize the results of studies. Generally, the independent variable goes on the x -axis (horizontal) and the dependent variable on the y -axis (vertical).

The type of visualization you use depends on the variable types in your research questions:

• A bar chart is ideal when you have a categorical independent variable.
• A scatter plot or line graph is best when your independent and dependent variables are both quantitative.

To inspect your data, you place your independent variable of treatment level on the x -axis and the dependent variable of blood pressure on the y -axis.

You plot bars for each treatment group before and after the treatment to show the difference in blood pressure.

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.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

• The type of soda – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

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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.

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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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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Dependent Variables (Definition + 30 Examples)

Welcome to a journey through the essential world of dependent variables! Whether you’re an avid learner, a seasoned researcher, or simply curious, unraveling the mysteries of dependent variables is crucial for making sense of scientific discoveries and everyday wonders.

A dependent variable is what we observe and measure in an experiment. It's called "dependent" because it changes based on the alterations we make to another variable, known as the independent variable. Think of it as a series of revealing clues, shedding light on the story of how one thing can affect another.

Embark with us on an enlightening adventure, as we delve into the significance of dependent variables, explore their relationship with independent variables, and uncover how they help us interpret and shape the world around us.

History of Dependent Variables

The concept of dependent variables finds its roots in the early foundations of scientific thought.

The ancient Greeks, notably Aristotle , laid down the groundwork for systematic observation and the study of cause and effect. Aristotle's ideas on causality, although different from today’s understanding, were pivotal in shaping the way we approach scientific inquiry.

Emergence of Experimental Science

The Renaissance period marked a significant shift in scientific thinking. Pioneers like Galileo Galilei and Sir Francis Bacon advocated for empirical observation and experimentation.

This period saw the emergence of experimental science, where the relationships between different variables, including dependent and independent ones, were systematically studied.

Development of Statistical Methods

The 18th and 19th centuries witnessed the development of statistical methods , which played a crucial role in understanding dependent variables.

Sir Francis Galton, a cousin of Charles Darwin, made significant contributions to the field of statistics and introduced the concept of regression, a foundational element in studying dependent variables.

Modern Day Applications

Today, the concept of dependent variables is integral to research across diverse fields, from biology and physics to psychology and economics. The evolution of research methodologies and statistical tools has allowed scientists and researchers to study dependent variables with increased precision and insight.

Conclusion on Origins

Understanding the origin of dependent variables offers a fascinating glimpse into the evolution of scientific thought and the relentless human pursuit of knowledge.

From the musings of ancient philosophers to the sophisticated research of today, dependent variables have journeyed through time, contributing to the rich tapestry of scientific discovery and progress.

What are Dependent Variables?

Understanding dependent variables is like piecing together a puzzle – it’s essential for seeing the whole picture! Dependent variables are at the core of scientific experiments, acting as the outcomes we observe and measure.

They respond to the changes we make in the independent variables , helping us unravel the connections and relationships between different elements in an experiment .

Dependent Variables in Scientific Experiments

In the realm of scientific experiments, dependent variables play the starring role of the outcome. When scientists alter something, the dependent variable is what reacts to this change.

For instance, if a botanist is examining how different amounts of sunlight (the independent variable) affect plant growth, the growth of the plant is the dependent variable.

Relationship with Independent Variables

Dependent variables and independent variables share a unique dance in the world of science. The independent variable leads, changing and altering, while the dependent variable follows, reacting and showing the effects of these changes.

It’s this intricate relationship that allows scientists and researchers to draw conclusions and make discoveries.

Making Observations and Drawing Conclusions

Observing dependent variables is like watching a story unfold. By carefully measuring and recording how they respond to changes, scientists can draw meaningful conclusions and answer pressing questions.

Whether it’s understanding how temperature affects sea levels or how diet influences health, dependent variables are the narrators of these scientific stories.

But remember, experimenters make errors, and sometimes those errors are based on their biases, or what they want to find or believe they will find, so keeping the variables in check is one way to avoid experimenter bias .

Real-World Applications

The insights gained from studying dependent variables don’t just stay in the lab – they ripple out into the real world!

From developing new medicines to improving educational techniques, understanding dependent variables is pivotal. They help us make informed decisions, solve problems, and enhance the quality of life for people around the globe.

Everyday Examples

In our everyday lives, we encounter countless instances of dependent variables.

When you adjust the brightness of your room to see how well you can read a book, the readability is your dependent variable.

Or, when a chef experiments with ingredients to observe the flavor of a dish, the taste is the dependent variable.

The Impact on Knowledge

Dependent variables are the building blocks of knowledge. They help us test hypotheses, validate theories, and expand our understanding of the universe.

Every observation, every measurement, brings us one step closer to unraveling the mysteries of the world and advancing human knowledge.

By grasping the role of dependent variables, we open doors to a myriad of possibilities, uncovering the secrets of the natural world and contributing to the rich tapestry of scientific discovery.

Dependent Variables in Research

Diving deeper into the realm of dependent variables, we uncover why they hold such an important role in the tapestry of scientific discovery and everyday life.

These variables are the storytellers, the revealers of effects, and the markers of change, helping us navigate the sea of knowledge and make waves of progress.

Scientific Discovery and Innovation

In the laboratory of discovery, dependent variables are the guiding stars. They help scientists and researchers observe the effects of changes, leading to breakthroughs and innovations.

Whether it’s finding a cure for a disease, inventing a new technology, or understanding the mysteries of the universe, dependent variables are at the heart of the eureka moments that shape our world.

Real-World Problem Solving

Outside the lab, the insights gained from dependent variables illuminate the path to solving real-world problems.

They play a crucial role in improving healthcare, education, environmental conservation, and numerous other fields, enabling us to develop solutions that enhance well-being and sustainability.

By understanding how dependent variables react, we can tailor strategies to address challenges and create a positive impact.

Informing Decision-Making

Every day, we make countless decisions, big and small. Dependent variables are like compasses, guiding our choices and actions.

Whether deciding on the best method to grow a garden, choosing a fitness routine, or selecting the right ingredients for a recipe, recognizing the dependent variables helps us make informed and effective decisions to achieve our goals.

Enhancing Understanding and Knowledge

The study of dependent variables enriches our comprehension of the world around us. They provide insights into cause and effect, helping us understand how different elements interact and influence each other.

This deepened understanding broadens our knowledge, fuels our curiosity, and inspires further exploration and learning.

Fostering Curiosity and Exploration

Peeling back the layers of dependent variables uncovers a world of wonder and curiosity. They invite us to ask questions, seek answers, and explore the intricate web of relationships in the natural and social world.

This sense of wonder and exploration drives scientific inquiry and fosters a lifelong love of learning and discovery.

Conclusion on Importance

The importance of dependent variables cannot be overstated. They are the keys that unlock the doors of understanding, the catalysts for innovation and progress, and the guides on our journey through the ever-evolving landscape of knowledge.

As we continue to explore and learn, the role of dependent variables remains central to our quest for understanding and discovery.

Challenges with Dependent Variables

While dependent variables illuminate the path of discovery, working with them can sometimes feel like navigating a labyrinth.

It’s essential to recognize the challenges and considerations that come with the territory, ensuring accurate, reliable, and meaningful outcomes in our pursuit of knowledge.

Measurement Accuracy

In the world of dependent variables, accuracy is king. Measuring outcomes precisely is crucial to avoid distorting the picture. Imagine trying to solve a puzzle with misshaped pieces – it wouldn’t fit together right! Ensuring accurate measurement means the story told by the dependent variable is true to reality.

External Influences

Sometimes, unseen forces can influence our dependent variables. These are called confounding variables , and they can sneak in and alter the outcomes, like a gust of wind turning the pages of a book.

Being aware of and controlling these external influences is essential to maintain the integrity of our observations and conclusions.

Consistency and Reliability

Consistency is the heartbeat of reliable results. When working with dependent variables, it’s vital to maintain consistent methods of measurement and observation. This consistency ensures that the story revealed is trustworthy and that the insights gained can be the foundation for further discovery and understanding.

Ethical Considerations

Exploring dependent variables also brings us face to face with ethical considerations . Whether it’s respecting privacy, ensuring safety, or acknowledging rights, it’s paramount to navigate the journey with integrity and responsibility. Ethical practices build trust and uphold the values that guide the pursuit of knowledge.

Varied Contexts and Applications

Dependent variables are versatile storytellers, revealing different tales in varied contexts and applications. Recognizing the diversity in application and interpretation is like tuning into different genres of stories – each holds unique insights and contributes to the richness of our understanding.

Reflection on Challenges and Considerations

Understanding and addressing the challenges and considerations in working with dependent variables is like sharpening the tools in our scientific toolbox. It strengthens the foundation of our exploration, ensuring that the journey is fruitful, the discoveries are genuine, and the stories told are authentic.

Famous Studies Involving Dependent Variables

The stage of scientific discovery has been graced by numerous studies and experiments where dependent variables played a starring role. These studies have shaped our understanding, answered profound questions, and paved the way for further exploration and innovation.

Ivan Pavlov’s Classical Conditioning

In the early 20th century, Ivan Pavlov ’s experiments with dogs shone a spotlight on dependent variables. He observed how dogs (the dependent variable) salivated in response to the sound of a bell (the independent variable), leading to groundbreaking insights into classical conditioning and learning.

Sir Isaac Newton’s Laws of Motion

Delving back into the 17th century, Sir Isaac Newton ’s exploration of the laws of motion involved observing how objects (the dependent variables) moved and interacted in response to forces (the independent variables). His work laid the foundations of classical mechanics and continues to influence science today .

Gregor Mendel’s Pea Plant Experiments

In the 19th century, Gregor Mendel ’s work with pea plants opened the doors to the world of genetics. By observing the traits of pea plants (the dependent variables) in response to different genetic crosses (the independent variables), Mendel unveiled the principles of heredity .

The Stanford Prison Experiment

In 1971, the Stanford Prison Experiment , led by Philip Zimbardo , explored the effects of perceived power and authority. The behavior of participants (the dependent variable) was observed in response to assigned roles as guards or prisoners (the independent variable), revealing insights into human behavior and ethics.

The Hawthorne Effect

In the 1920s and 1930s, studies at the Western Electric Hawthorne Works in Chicago observed worker productivity (the dependent variable) in response to changes in working conditions (the independent variables). This led to the discovery of the Hawthorne Effect , highlighting the influence of observation on human behavior.

Reflection on Famous Studies

These famous studies and experiments spotlight the pivotal role of dependent variables in scientific discovery. They illustrate how observing and measuring dependent variables have expanded our knowledge, led to breakthroughs, and addressed fundamental questions about the natural and social world.

Examples of Dependent Variables

1) test scores.

In an educational setting, student test scores often serve as a dependent variable to measure academic achievement.

2) Heart Rate

In health and exercise science, heart rate can be a dependent variable indicating cardiovascular response to activity.

3) Plant Growth

In botany, the growth of plants can be observed as a dependent variable when studying the effects of different environmental conditions.

4) Sales Revenue

In business, sales revenue may be a dependent variable analyzed in relation to advertising strategies.

5) Blood Pressure

In medicine, blood pressure levels can be a dependent variable to study the effects of medication or diet.

6) Job Satisfaction

In organizational psychology, job satisfaction levels of employees may be the dependent variable.

7) Ice Melt Rate

In climate studies, the rate at which ice melts can be a dependent variable in relation to temperature changes.

8) Customer Satisfaction

In service industries, customer satisfaction levels are often the dependent variable.

9) Reaction Time

In psychology, an individual's reaction time can be measured as a dependent variable in cognitive studies.

10) Fuel Efficiency

In automotive studies, the fuel efficiency of a vehicle may be the dependent variable.

11) Population Size

In ecology, the size of animal or plant populations can be a dependent variable.

12) Productivity Levels

In the workplace, employee productivity can be observed as a dependent variable.

13) Immune Response

In immunology, the body’s immune response can be the dependent variable when studying vaccines or infections.

14) Enzyme Activity

In biochemistry, the activity levels of enzymes can be measured as a dependent variable.

15) Market Share

In business, a company’s market share can be the dependent variable in relation to competition strategies.

16) Voter Turnout

In political science, voter turnout can be a dependent variable studied in relation to campaign efforts.

17) Concentration Levels

In cognitive studies, individual concentration levels can be measured as a dependent variable.

18) Pollution Levels

In environmental science, levels of pollution can be a dependent variable in relation to industrial activity.

19) Reading Comprehension

In education, students’ reading comprehension can be the dependent variable.

20) Muscle Strength

In kinesiology, an individual’s muscle strength can be measured as a dependent variable.

21) Website Traffic

In digital marketing, the traffic a website receives can be the dependent variable.

22) Patient Recovery Time

In healthcare, the recovery time of patients can be observed as a dependent variable.

23) Student Attendance

In education, student attendance rates can be a dependent variable.

24) Rainfall Amounts

In meteorology, the amount of rainfall can be a dependent variable.

25) Consumer Spending

In economics, consumer spending levels can be observed as a dependent variable.

26) Energy Consumption

In energy studies, the amount of energy consumed can be a dependent variable.

27) Body Mass Index (BMI)

In health studies, an individual’s BMI can be measured as a dependent variable.

28) Employee Retention

In human resources, employee retention rates can be the dependent variable.

29) Water Quality

In environmental studies, the quality of water can be observed as a dependent variable.

30) Customer Loyalty

In business, customer loyalty can be a dependent variable in relation to brand reputation and service quality.

These examples illustrate the diverse nature of dependent variables and how they are used to measure outcomes across a multitude of disciplines and scenarios.

Real-World Examples of Dependent Variables

Dependent variables are not just confined to textbooks; they dance through our daily lives, telling tales of change and effect. Let’s take a closer look at some real-life scenarios where dependent variables play a key role in telling the story of cause and effect.

In healthcare, dependent variables help doctors and researchers understand the effects of treatments and interventions.

For example, a patient’s blood sugar level is a dependent variable when studying the effectiveness of diabetes medication. Monitoring this variable helps healthcare professionals tailor treatments and manage health conditions effectively.

In the realm of education, dependent variables like test scores and attendance rates help educators gauge the effectiveness of teaching methods and interventions.

By observing these variables, teachers can adapt their strategies to enhance student learning and well-being.

Environmental Conservation

In the world of environmental conservation, dependent variables such as animal population sizes and pollution levels provide insights into the impact of conservation efforts.

These observations guide strategies to protect ecosystems and biodiversity, ensuring a harmonious balance between humans and nature.

Technology and Innovation

In the field of technology and innovation, dependent variables like user engagement and product performance are crucial in developing and refining groundbreaking technologies.

Observing these variables enables innovators to optimize designs, improve user experiences, and drive progress in the digital age.

Fitness and Well-being

In the pursuit of fitness and well-being, dependent variables such as muscle strength and heart rate are observed to measure the effects of different exercise routines and dietary choices.

These observations guide individuals in achieving their health and fitness goals, fostering a sense of well-being and vitality.

Social Sciences

In social sciences, dependent variables like voter turnout and job satisfaction offer insights into human behavior and societal dynamics. Studying these variables helps researchers and policymakers understand societal trends, human motivations, and the intricate tapestry of social interactions.

Business and Economics

In the business and economic landscape, dependent variables such as sales revenue and consumer spending reveal the effectiveness of marketing strategies and economic policies.

Analyzing these variables helps businesses and governments make informed decisions, fueling economic growth and prosperity.

Culinary Arts

In culinary arts, dependent variables like taste and texture are observed to perfect recipes and culinary creations. Chefs experiment with ingredients and cooking techniques, using the feedback from these variables to craft delightful culinary experiences.

Arts and Entertainment

In arts and entertainment, audience reception and ticket sales are dependent variables that offer insights into the appeal of creative works. Artists and creators use this feedback to hone their craft, create meaningful connections with the audience, and contribute to the rich tapestry of culture and creativity.

Conclusion on Real-Life Applications

Exploring the real-life scenarios and applications of dependent variables brings to light the omnipresence and significance of these variables in shaping our world.

From healthcare to the arts, understanding and observing dependent variables enable us to learn, adapt, and thrive in a constantly evolving environment.

Identifying Dependent Variables

Spotting a dependent variable might seem like looking for a needle in a haystack, but with the right tools and know-how, it becomes a fascinating treasure hunt!

Knowing how to identify dependent variables is essential whether you’re conducting an experiment, analyzing data, or just curious about the relationships between different factors.

To be a true dependent variable detective, let’s revisit its definition: a dependent variable is what we measure in an experiment and what changes in response to the independent variable. It’s like the echo to a shout, the reaction to an action.

Relationship with Changes

In the dance of variables, the dependent variable is the one that responds. When something is tweaked, adjusted, or altered (that’s the independent variable), the dependent variable is what shows the effect of those changes. It’s the piece of the puzzle that helps us see the bigger picture.

Tips and Tricks for Identification

Identifying dependent variables can be a breeze with a few handy tips!

First, ask yourself, “What am I measuring or observing?” This is usually your dependent variable.

Next, look for the effect or change that is happening as a result of manipulating something else.

If you’re still unsure, try to phrase your observation as “If we change X, then Y will respond.” Y is typically the dependent variable.

Practice Makes Perfect: Scenarios

Let’s put our knowledge to the test! Can you spot the dependent variables in these scenarios?

• Cooking Time: You’re experimenting with cooking times to see how soft the cookies become.
• Exercise Routine: Trying out different types of exercise routines to see which one increases your stamina the most.
• Plant Fertilizer: Applying different types of fertilizers to your tomato plants to observe which one produces the juiciest tomatoes.
• Study Environment: Testing various study environments to identify which one improves your focus and learning.
• Sleep Duration: Adjusting the number of hours you sleep to observe its impact on your energy level the next day.

Answers and Explanation

Got your answers ready? Let’s see how you did!

• Cooking Time: The softness of the cookies is the dependent variable.
• Exercise Routine: The increase in stamina is what you are measuring, making it the dependent variable.
• Plant Fertilizer: The juiciness of the tomatoes is the dependent variable here.
• Study Environment: Your focus and learning are the dependent variables in this scenario.
• Sleep Duration: The energy level the next day is your dependent variable.

Identifying dependent variables is a skill that sharpens with practice, helping us unravel the wonders of cause and effect in the world around us.

Final Thoughts on Identification

Mastering the art of identifying dependent variables is like gaining a superpower. It allows us to see the world through a lens of relationships and effects, deepening our understanding of how changes in one element can impact another.

In the intricate dance of cause and effect, dependent variables tell tales of outcomes, changes, and responses. From the realm of science to the canvas of art, they shape our understanding of the world and drive progress in countless fields.

The challenges faced in measuring these variables only add layers to their complexity, but the pursuit of knowledge and the joy of discovery make every step of the journey worthwhile.

As we conclude our exploration of dependent variables, we leave with a sense of wonder and curiosity, equipped with the knowledge to observe, question, and explore the world around us.

The stories of dependent variables continue to unfold, and the adventure of learning and discovery is boundless.

Thank you for joining us on this enlightening journey through the world of dependent variables. Keep exploring, stay curious, and continue to marvel at the wonders of the world we live in!

Related posts:

• Independent Variables (Definition + 43 Examples)
• Confounding Variable in Psychology (Examples + Definition)
• Positive Correlation (Meaning + 39 Examples + Quiz)
• 19+ Experimental Design Examples (Methods + Types)
• 45+ Negative Correlation Examples (Definition + Use-cases)

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Independent and Dependent Variables: Which Is Which?

General Education

Independent and dependent variables are important for both math and science. If you don't understand what these two variables are and how they differ, you'll struggle to analyze an experiment or plot equations. Fortunately, we make learning these concepts easy!

In this guide, we break down what independent and dependent variables are , give examples of the variables in actual experiments, explain how to properly graph them, provide a quiz to test your skills, and discuss the one other important variable you need to know.

What Is an Independent Variable? What Is a Dependent Variable?

A variable is something you're trying to measure. It can be practically anything, such as objects, amounts of time, feelings, events, or ideas. If you're studying how people feel about different television shows, the variables in that experiment are television shows and feelings. If you're studying how different types of fertilizer affect how tall plants grow, the variables are type of fertilizer and plant height.

There are two key variables in every experiment: the independent variable and the dependent variable.

Independent variable: What the scientist changes or what changes on its own.

Dependent variable: What is being studied/measured.

The independent variable (sometimes known as the manipulated variable) is the variable whose change isn't affected by any other variable in the experiment. Either the scientist has to change the independent variable herself or it changes on its own; nothing else in the experiment affects or changes it. Two examples of common independent variables are age and time. There's nothing you or anything else can do to speed up or slow down time or increase or decrease age. They're independent of everything else.

The dependent variable (sometimes known as the responding variable) is what is being studied and measured in the experiment. It's what changes as a result of the changes to the independent variable. An example of a dependent variable is how tall you are at different ages. The dependent variable (height) depends on the independent variable (age).

An easy way to think of independent and dependent variables is, when you're conducting an experiment, the independent variable is what you change, and the dependent variable is what changes because of that. You can also think of the independent variable as the cause and the dependent variable as the effect.

It can be a lot easier to understand the differences between these two variables with examples, so let's look at some sample experiments below.

Examples of Independent and Dependent Variables in Experiments

Below are overviews of three experiments, each with their independent and dependent variables identified.

Experiment 1: You want to figure out which brand of microwave popcorn pops the most kernels so you can get the most value for your money. You test different brands of popcorn to see which bag pops the most popcorn kernels.

• Independent Variable: Brand of popcorn bag (It's the independent variable because you are actually deciding the popcorn bag brands)
• Dependent Variable: Number of kernels popped (This is the dependent variable because it's what you measure for each popcorn brand)

Experiment 2 : You want to see which type of fertilizer helps plants grow fastest, so you add a different brand of fertilizer to each plant and see how tall they grow.

• Independent Variable: Type of fertilizer given to the plant
• Dependent Variable: Plant height

Experiment 3: You're interested in how rising sea temperatures impact algae life, so you design an experiment that measures the number of algae in a sample of water taken from a specific ocean site under varying temperatures.

• Independent Variable: Ocean temperature
• Dependent Variable: The number of algae in the sample

For each of the independent variables above, it's clear that they can't be changed by other variables in the experiment. You have to be the one to change the popcorn and fertilizer brands in Experiments 1 and 2, and the ocean temperature in Experiment 3 cannot be significantly changed by other factors. Changes to each of these independent variables cause the dependent variables to change in the experiments.

Where Do You Put Independent and Dependent Variables on Graphs?

Independent and dependent variables always go on the same places in a graph. This makes it easy for you to quickly see which variable is independent and which is dependent when looking at a graph or chart. The independent variable always goes on the x-axis, or the horizontal axis. The dependent variable goes on the y-axis, or vertical axis.

Here's an example:

As you can see, this is a graph showing how the number of hours a student studies affects the score she got on an exam. From the graph, it looks like studying up to six hours helped her raise her score, but as she studied more than that her score dropped slightly.

The amount of time studied is the independent variable, because it's what she changed, so it's on the x-axis. The score she got on the exam is the dependent variable, because it's what changed as a result of the independent variable, and it's on the y-axis. It's common to put the units in parentheses next to the axis titles, which this graph does.

There are different ways to title a graph, but a common way is "[Independent Variable] vs. [Dependent Variable]" like this graph. Using a standard title like that also makes it easy for others to see what your independent and dependent variables are.

Are There Other Important Variables to Know?

Independent and dependent variables are the two most important variables to know and understand when conducting or studying an experiment, but there is one other type of variable that you should be aware of: constant variables.

Constant variables (also known as "constants") are simple to understand: they're what stay the same during the experiment. Most experiments usually only have one independent variable and one dependent variable, but they will all have multiple constant variables.

For example, in Experiment 2 above, some of the constant variables would be the type of plant being grown, the amount of fertilizer each plant is given, the amount of water each plant is given, when each plant is given fertilizer and water, the amount of sunlight the plants receive, the size of the container each plant is grown in, and more. The scientist is changing the type of fertilizer each plant gets which in turn changes how much each plant grows, but every other part of the experiment stays the same.

In experiments, you have to test one independent variable at a time in order to accurately understand how it impacts the dependent variable. Constant variables are important because they ensure that the dependent variable is changing because, and only because, of the independent variable so you can accurately measure the relationship between the dependent and independent variables.

If you didn't have any constant variables, you wouldn't be able to tell if the independent variable was what was really affecting the dependent variable. For example, in the example above, if there were no constants and you used different amounts of water, different types of plants, different amounts of fertilizer and put the plants in windows that got different amounts of sun, you wouldn't be able to say how fertilizer type affected plant growth because there would be so many other factors potentially affecting how the plants grew.

3 Experiments to Help You Understand Independent and Dependent Variables

If you're still having a hard time understanding the relationship between independent and dependent variable, it might help to see them in action. Here are three experiments you can try at home.

Experiment 1: Plant Growth Rates

One simple way to explore independent and dependent variables is to construct a biology experiment with seeds. Try growing some sunflowers and see how different factors affect their growth. For example, say you have ten sunflower seedlings, and you decide to give each a different amount of water each day to see if that affects their growth. The independent variable here would be the amount of water you give the plants, and the dependent variable is how tall the sunflowers grow.

Experiment 2: Chemical Reactions

Explore a wide range of chemical reactions with this chemistry kit . It includes 100+ ideas for experiments—pick one that interests you and analyze what the different variables are in the experiment!

Experiment 3: Simple Machines

Build and test a range of simple and complex machines with this K'nex kit . How does increasing a vehicle's mass affect its velocity? Can you lift more with a fixed or movable pulley? Remember, the independent variable is what you control/change, and the dependent variable is what changes because of that.

Quiz: Test Your Variable Knowledge

Can you identify the independent and dependent variables for each of the four scenarios below? The answers are at the bottom of the guide for you to check your work.

Scenario 1: You buy your dog multiple brands of food to see which one is her favorite.

Scenario 2: Your friends invite you to a party, and you decide to attend, but you're worried that staying out too long will affect how well you do on your geometry test tomorrow morning.

Scenario 3: Your dentist appointment will take 30 minutes from start to finish, but that doesn't include waiting in the lounge before you're called in. The total amount of time you spend in the dentist's office is the amount of time you wait before your appointment, plus the 30 minutes of the actual appointment

Scenario 4: You regularly babysit your little cousin who always throws a tantrum when he's asked to eat his vegetables. Over the course of the week, you ask him to eat vegetables four times.

Summary: Independent vs Dependent Variable

Knowing the independent variable definition and dependent variable definition is key to understanding how experiments work. The independent variable is what you change, and the dependent variable is what changes as a result of that. You can also think of the independent variable as the cause and the dependent variable as the effect.

When graphing these variables, the independent variable should go on the x-axis (the horizontal axis), and the dependent variable goes on the y-axis (vertical axis).

Constant variables are also important to understand. They are what stay the same throughout the experiment so you can accurately measure the impact of the independent variable on the dependent variable.

What's Next?

Independent and dependent variables are commonly taught in high school science classes. Read our guide to learn which science classes high school students should be taking.

Scoring well on standardized tests is an important part of having a strong college application. Check out our guides on the best study tips for the SAT and ACT.

Interested in science? Science Olympiad is a great extracurricular to include on your college applications, and it can help you win big scholarships. Check out our complete guide to winning Science Olympiad competitions.

Quiz Answers

1: Independent: dog food brands; Dependent: how much you dog eats

2: Independent: how long you spend at the party; Dependent: your exam score

3: Independent: Amount of time you spend waiting; Dependent: Total time you're at the dentist (the 30 minutes of appointment time is the constant)

4: Independent: Number of times your cousin is asked to eat vegetables; Dependent: number of tantrums

These recommendations are based solely on our knowledge and experience. If you purchase an item through one of our links, PrepScholar may receive a commission.

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Dependent Variable Definition and Examples

The dependent variable is the variable that you study and measure in response to changes in the independent variable . In other words, it depends on the independent variable. Other names for the dependent variable are the responding variable or measured variable.

Dependent Variable Examples

For example, say you want to know whether the amount you eat changes from day to day. You can set this up as an experiment in which you record food ingested over time. You add up all the calories you eat during a day or you measure the mass of food per day. To get meaningful data, you carry out the project for a month. The amount of food depends on the day, so it is the dependent variable.

For another example, you decide to see whether heart rate is affected by temperature. In other words, if you change the temperature, then does it affect your heart rate? Temperature is the independent variable or the one you control. Your heart rate is the dependent variable, which you measure in response to a change in temperature.

How to Identify the Dependent Variable

To find the dependent variable, think of the experiment in terms of “if, then” or “cause and effect.” The dependent variable is the “then” or “effect.” If you change one thing (the independent variable), then there is a change in the other thing (the dependent variable). You can set or control the independent variable, but you can only observe and measure the dependent variable.

Graphing the Dependent Variable

When graphing data, the convention is to put the independent variable on the x-axis and the dependent variable on the y-axis. If you write an ordered pair to record data, the independent variable is given first, followed by the dependent variable [e.g., (0, 2)].

The acronym to remember is DRY:

D – Dependent variable R – Responds to change Y – Y-axis on a graph

• Hinkelmann, Klaus; Kempthorne, Oscar (2008).  Design and Analysis of Experiments. Volume I: Introduction to Experimental Design  (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
• Quine, Willard V. (1960). “ Variables Explained Away .” Proceedings of the American Philosophical Society. American Philosophical Society. 104 (3): 343–347.

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Dependent Variable vs. Independent Variable: What Is the Difference?

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A dependent variable is the variable being tested in a scientific experiment.

The dependent variable is "dependent" on the independent variable. As the experimenter changes the independent variable, the change in the dependent variable is observed and recorded. When you take data in an experiment, the dependent variable is the one being measured.

Common Misspellings: Dependant variable

Dependent Variable Examples

• A scientist is testing the effect of light and dark on the behavior of moths by turning a light on and off. The independent variable is the amount of light and the moth's reaction is the dependent variable . A change in the independent variable ( amount of light ) directly causes a change in the dependent variable (moth behavior).
• You want to learn which kind of chicken produces the largest eggs . The egg size depends on the chicken breed, so breed is the independent variable and egg size is the dependent variable.
• You want to know whether or not stress affects heart rate . Your independent variable is the stress, while the dependent variable is heart rate . To experiment, you would provide stress and measure the subject's heartbeat . In a good experiment, you'd choose a stress you could control and quantify. Your choice could lead you to perform additional experiments since it might turn out that the change in heart rate after exposure to a decrease in temperature by 40 degrees ( physical stress ) might be different from the heart rate after failing a test ( psychological stress ). Even though your independent variable might be a number you measure, it's one you control, so it's not "dependent."

Distinguishing Between Dependent and Independent Variables

Sometimes it's easy to tell the two types of variables apart , but if you get confused, here are tips to help keep scientific variables straight:

• If you change one variable, which is affected? If you're studying the growth rate of plants using different fertilizers , can you identify the variables? Start by thinking about what you are controlling and what you will be measuring. The type of fertilizer is the independent variable. The rate of growth is the dependent variable. So, to experiment, you would fertilize plants with one fertilizer and measure the change in height of the plant over time, then switch fertilizers and measure the height of plants over the same period. You might be tempted to identify time or height as your variable, not the growth rate (distance per time). It may help to look at your hypothesis or purpose to remember your goal .
• Write out your variables as a sentence stating cause and effect. The independent variable causes a change in the dependent variable. Usually, the sentence won't make sense if you get them wrong. For example: (Taking vitamins) affects the number of (birth defects). = Makes sense. (Birth defects) affects the number of (vitamins). = Probably not much.

Graphing the Dependent Variable

When you graph data, the independent variable is on the X-axis, while the dependent variable is on the Y-axis. You can use the DRY MIX acronym to remember this:

D - dependent variable R - responds to change Y - Y-axis

M - manipulated variable (one you change) I - independent variable X - X-axis

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What Are Independent & Dependent Variables in Science for Kids?

What Is a Responding Variable in Science Projects?

Although children may be too young to be familiar with the methods for experimentation, they are not too young to understand the meaning of the concepts. If you can explain and demonstrate the concepts underlying the scientific method in an age-appropriate way, kids can grasp how it works. With your help and a few basic rules in scientific experimentation, a child can run her own simple experiments.

What is a Variable?

A “variable” is a word for a quantity or condition that can change. Variables can be continuous or they can be discrete. Continuous variables can have many values. For example, time is continuous and can have many values. Plant growth, amount of sunlight or amount of water flowing are all continuous variables. Discrete variables are ones that have a few, distinct values. Something can be either on or off, present or absent, or have only several countable possibilities. A kitchen light can be on or off or a person may have blue, brown, green or hazel eyes.

Independent Variable

An independent variable is a variable that you can control. One way to explain it to a child is that it is the variable that the child can change during the experiment. For example, in an experiment on the effect of light on plant growth, the child can control how much light a plant receives. He can put one plant near a window and another plant in a dark closet.

Dependent Variable

A dependent variable is the variable that you observe and measure. You have no control over the dependent variable; you want to observe what happens to the dependent variable when you change the independent variable. For example, if the child is testing the effects of light on plant growth, how much the plant grows after some period of time would be the dependent variable. The child can measure how much the plant in the closet grows relative to how much the plant near the window grows.

Controlled Variables

Besides independent and dependent variables, every good experiment needs to control certain variables so that they do not influence the outcome of the experiment systematically. A controlled variable is one that you keep the same for all the conditions of your experiment. A good scientist needs to think through all the variables that might need to be controlled so that they do not interfere with the experiment. For example, to get reliable results for the plant experiment, both the plant near the window and the plant in the closet need to receive the same amount of water so that testers would know that it was the differences in light and not the differences in water that made one plant grow more than the other.

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• National Center for Education Statistics: What are Independent and Dependent Variables?
• Science Buddies: Variables in your Science Fair Project

About the Author

Danielle Cort has been a freelance writer since 2008, specializing in psychology, health, education and parenting. She has published articles in "Family" magazine. Before becoming a freelance writer, Cort worked in the public policy research sector, conducting research, creating surveys and budgets. She holds a Doctor of Philosophy in social psychology from the University of Massachusetts.

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Independent, Dependent and Controlled Variables

This is part of the NSW HSC science curriculum part of the Working Scientifically skills.

What are Independent, Dependent, and Controlled Variables?

As a high school science student, you are likely to come across different types of variables in your experiments. Being able to recognise these variables is a skill which is included in the NSW Higher School Certificate (HSC) curriculum. These variables are essential to scientific inquiry as they help us understand how different factors affect the outcomes of experiments. There are three main types of variables in scientific investigations: independent, dependent, and controlled variables. We will explore each of these variables and their importance in scientific inquiry. 

Independent Variables

Independent variables are the variables that are manipulated or changed by the researcher in an experiment. They are also known as the input variables or the cause variables because they are the factors that cause changes in the dependent variable.

For example, if you were investigating the effect of temperature on the rate of photosynthesis in plants, temperature would be the independent variable. You would manipulate the temperature to see how it affects the rate of photosynthesis.

It is essential to note that an experiment should have only one independent variable. This is because if you change more than one variable, you will not know which variable caused the change in the dependent variable. Therefore, by controlling the independent variable, you can determine the effect of that variable on the dependent variable.

Dependent variables

Dependent variables are the variables that are affected by the independent variable in an experiment. They are also known as the outcome variables or the effect variables. The dependent variable is what you measure or observe to determine the effect of the independent variable.

For example, in the temperature and photosynthesis experiment, the dependent variable would be the rate of photosynthesis, which is affected by changes in temperature.

It is crucial to keep the dependent variable constant during an experiment to ensure that any changes observed are a result of changes in the independent variable. Additionally, the dependent variable should be measurable and quantitative, meaning that it can be expressed in numerical values.

Controlled variables

Controlled variables are the variables that are kept constant during an experiment to ensure that they do not affect the outcome. These variables are also known as constant variables or the controlled factors. The purpose of controlling these variables is to ensure that any changes observed in the dependent variable are due to changes in the independent variable and not due to other factors.

For example, in the temperature and photosynthesis experiment, the controlled variables would include factors such as the type of plant, the amount of light, and the amount of carbon dioxide. By keeping these variables constant, you can ensure that any changes in the rate of photosynthesis are due to changes in temperature and not due to other factors.

Identifying variables

Let's consider a scenario where we want to investigate the effect of different amounts of water on plant growth. In this case:

Independent variable: The independent variable in this experiment is the amount of water used to water the plants. We could use different amounts of water, such as 100 ml, 200 ml, or 300 ml.

Dependent variable: The dependent variable is still the growth of the plants, which we could measure by tracking the height, weight, or number of leaves of the plants.

Controlled variables: Some controlled variables in this experiment might include the type and species of plants used, the type and amount of soil used, the size and type of pots used, and the amount of sunlight and temperature that the plants are exposed to.

By identifying and controlling these variables, we can design a more controlled and rigorous experiment to investigate the effect of different amounts of water on plant growth.

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