Understanding the language of research - Variables

 In practice, the term variable is used as a synonym for construct, or the property being studied. In this
context, a variable is a symbol of an event, act, characteristic, trait, or attribute that can be measured
and to which we assign values.

1. 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

Example: Independent and dependent variables.You design a study to test whether changes in room temperature have an effect on math test scores.

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.

Your dependent variable is math test scores. You measure the math skills of all participants using a standardized test and check whether they differ based on room temperature.

What is an independent variable?

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.

Types of independent variables

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.

What is a dependent variable?

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.

Identifying independent vs. dependent variables

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?

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

Research question	Independent variable	Dependent variable(s)
Do tomatoes grow fastest under fluorescent, incandescent, or natural light?	Type of light the tomato plant is grown under	The rate of growth of the tomato plant
What is the effect of intermittent fasting on blood sugar levels?	Presence or absence of intermittent fasting	Blood sugar levels
Is medical marijuana effective for pain reduction in people with chronic pain?	Presence or absence of medical marijuana use	Frequency of pain Intensity of pain
To what extent does remote working increase job satisfaction?	Type of work environment (remote or in office)	Job satisfaction self-reports

 2. Moderating or Interaction Variables

In actual study situations, however, such a simple one-to-one relationship needs to be conditioned or revised to take other variables into account. Often, we can use another type of explanatory variable that is of value here: the moderating variable (MV). A moderating or interaction variable is a second independent variable that is included because it is believed to have a significant contributory or contingent effect on the original IV–DV relationship.

3. Extraneous Variables

In an experiment, an extraneous variable is any variable that you’re not investigating that can potentially affect the outcomes of your research study.

If left uncontrolled, extraneous variables can lead to inaccurate conclusions about the relationship between independent and dependent variables. They can also introduce a variety of research biases to your work, particularly selection bias.

Extraneous variables can threaten the internal validity of your study by providing alternative explanations for your results.

When extraneous variables are uncontrolled, it’s hard to determine the exact effects of the independent variable on the dependent variable, because the effects of extraneous variables may mask them.

Uncontrolled extraneous variables can also make it seem as though there is a true effect of the independent variable in an experiment when there’s actually none.

What is a confounding variable?

Confounding variables (a.k.a. confounders or confounding factors) are a type of extraneous variable that are related to a study’s independent and dependent variables. A variable must meet two conditions to be a confounder:

• It must be correlated with the independent variable. This may be a causal relationship, but it does not have to be.
• It must be causally related to the dependent variable.

 A control variable is anything that is held constant or limited in a research study. It’s a variable that is not of interest to the study’s objectives, but is controlled because it could influence the outcomes.

4. Intervening Variables

An intervening variable is a variable that handles the change in the dependent variable due to the change in the independent variable. In other words, the outcome of the dependent variable is decided through the intervening variable, which itself gets influenced by the independent variable.