If you are carrying out scientific research, chances are that you will need to deal with independent and dependent variables. If you want to receive a valid outcome, it’s important that you identify a correct relationship between these two factors. Confusing basic terms may compromise your entire study. 

Read this guide to find out:

  • What are independent and dependent variables?
  • What is the difference between them?
  • How to determine the correlation between them?

We’ll show you what factors make them differ and give examples of both types. Let’s get started! 

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Difference Between Independent and Dependent Variables

A variable in research is a value that can be measured. Typically, there are two main types of factors that we can study in any scientific research: independent and dependent variables. They create a causal relationship and play a special role in an experiment. Let’s define each term to understand the main difference. 

  • Independent variable It is a supposed cause. It’s not affected by other factors involved in your study.
  • Dependent variable It is a supposed effect. Its value may change under the influence of an independent factor.

As it’s clear from this definition, the main difference between an independent and dependent variable is that the one affects the other one. Independent units are specially chosen or changed by an experimenter. However, they do not depend on the reaction, properties or intentions of any other object. In contrast, dependent units can change and, as such, are measured and recorded during an experiment.

Independent and Dependent Variables: Examples

Let us give you some examples of independent and dependent variables in research studies, just to make you understand. Both factors can be used in very different investigations: psychological, biological, sociological, physical, and so on. Look at some examples below to gain more insights.

Research QuestionIndependent UnitDependent Unit
Does fur of a laboratory rat change from omega-3 and omega-6 fats?Type of vitamins rats are takingLength, density, or luster of rat’s fur
Who has a higher level of happiness – residents of megacities or small towns?City sizeParticipant’s level of happiness
How does salinity of water affect its electrical conductivity?Amount of salt in waterWater electrical conductivity
Does academic progress depend on increased learning time?Number of hours students studyTest score

In each case, we can see that values of “effects” directly rely on parameters controlled or chosen by a researcher.

How to Identify Independent and Dependent Variables

To identify independent and dependent variables, try to reimagine your study as a root and consequence. Think in terms of a so-called “cause-and-effect approach”. Then, try to determine a causal relationship between 2 or more subjects you compare. Sometimes, you may have more than one dependent factor. In this case, you will need to add all effects to your research design. 

Note: Independent variables can be easily confused with confounding variables which may distort your study’s results. A confounder influences an effect but is also related to its cause.

Dependent and Independent Variables in Research: Uses

There are different ways to use independent and dependent variables in research. The most common cases are experiments. But sometimes, these factors may take place in non-experimental research. Each kind of study requires a special approach. Let’s discuss the uses of both factors in different types of research.

Independent and Dependent Variables In Experimental Analysis

In experiments with independent and dependent variables, a researcher manipulates the cause and tries to measure its effect on the dependent factor. Let’s look at an example below to see how this causal relationship works in an experimental study.


You examine the influence of carcinogenic agents contained in multiple substances. To measure the effects, each of them is applied to an ear of a laboratory rat in the same dose and concentration once per day during 1 month. Skin reaction at the contact spot is monitored. If after 1 month none of the animals develops a tumor, concentration of all substances is doubled and experiment is extended for another month.


  • Supposed causes manipulated in this experiment are timing, dose of substance and concentration. You need to measure the presence of skin reactions.
  • Supposed effects are skin quality in contact area and damage level.
  • Outcome will show us which substance is the most dangerous.

Independent and Dependent Variables in Non-Experimental Research

You may also need to find independent and dependent variables in non-experimental research. If you are working with a causal relationship in other types of study, keep in mind that you won’t be able to manipulate your factors. While carrying out a non-experimental research, you will be looking for any a cause-and-effect relationship that already exists.


An experimenter wants to find out whether economic globalization causes income inequality. A researcher can’t measure economic globalization. Instead, they will be comparing the effect of globalization on inequality by years.


  • Independent variable is economic globalization; it can’t be controlled.
  • Effect is the level of income.
  • Comparison by years will show whether globalization indeed leads to unequal distribution of income.

In non-experimental research, a causal relationship may not be obvious. There may be other factors involved and, as such, your study’s results may be invalid. These agents are called confounding variables.

In some cases when a cause-and-effect relationship is not that evident, you may want to look for other variations of independent and dependent variables. Below you can find some other names for both units.

Right-hand-side Left-hand-side

Independent and Dependent Variables on a Graph

If your studies require illustrations, graphing independent and dependent variables could be a good idea. Let us briefly explain how to do this.

Typically, parameters of an independent unit are those values along the X axis (horizontal one), while the values of a dependent factor appear on the Y axis (vertical one). Shape of your graph depends on your survey data. For example, if your experiment shows a direct correlation, then a linear graph tends to a straight line coming out of point 0.

Bottom Line

Independent and dependent variables are two key factors in scientific experiments and other types of investigations. Independent factors stand alone. They can be controlled by an experimenter. Dependent subjects are those units that change due to independent factors.

These two variables have a causal relationship – we can observe a direct correlation between a cause and an effect.

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FAQ About Independent and Dependent Variables

1. Can an independent variable also be dependent?

No, an independent variable can not also be dependent in the same study. The former stands alone and its value is known before an experiment. The latter can change under some influence of an independent factor, so it’s measured during an experiment. These two conditions cannot be used interchangeably.

2. Can I use more than one independent or dependent variable in research?

Yes, you can use as many independent and dependent variables as you need in your study. Multiple variables appear if you have a complex phenomena to study. Some objects or events may produce various effects, so you will need to include all factors in your study. Likewise, you may work with several causes. But in this case you need to design several research questions.

3. What are some examples of variables in Psychology?

Independent and dependent variables in Psychology are changes of reality that can be measured in some way. Experimenters can consider gender, age, income level, psychological method, incentive conditions as independent factors. Any psychological phenomena caused by these factors will be dependent factors.

Article posted on:Aug 2, 2022
Article updated on:Aug 2, 2022


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