What Is an Independent Variable? (and How to Identify One)
By Indeed Editorial Team
Updated November 29, 2022
Published December 7, 2021
The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.
In research, variables are objects, events, ideas, or feelings with changing quantities and qualities. While many variable types exist, research studies typically include independent variables. By learning what independent variables are and how to identify them, you can better understand how to control the results you obtain from research studies. In this article, we answer the question, "What is an independent variable?" discuss identifying independent and dependent variables, present other essential variable types, and show several examples.
What is an independent variable?
To answer the question, "What is an independent variable?" it helps to first understand that it's a variable that doesn't change its value with changes in other variables you measure. For example, your age is often an independent variable because it doesn't change with other factors, like what you eat, how long you watch television, or where you live. Researchers typically define independent and dependent variables when conducting experiments. Unlike a dependent variable which describes a study's purpose, independent variables change their values due to external factors or a researcher's actions.
For example, suppose you're studying how plants grow when exposed to varying rainfall levels. In this case, the amount of rainfall measured per hour is an independent variable that changes because of external factors, not the growth pattern. An independent variable typically affects a dependent variable, making it crucial to select suitable independent variables for your experiment. For example, the number of hours you sleep daily is an independent variable because it can affect your focus at work, which is a dependent variable.
Identifying independent and dependent variables
Here are useful tips to help you determine whether a variable is independent or dependent:
Determine whether you can control the variable. If you don't have direct control over the variable during a study, it's an independent variable.
Assess what causes the variable to change. If the variable's value doesn't change as you change other variables, it's an independent variable.
Observe how the variable changes. Adjust the variables to determine which you can control.
Other essential types of variables
Aside from independent and dependent variables, here are other variable types in research studies:
This type of variable helps you explain the relationship between two other variables. For example, suppose your study uses education level as an independent variable to predict spending, which is the dependent variable. In that case, an individual's income might be the intervening variable describing the relationship between education and spending.
A moderating variable changes the relationship between independent and dependent variables by impacting the intervening variable's effect. For example, suppose a study predicts how frequently patients get physical exams and uses economic status as its independent variable. The relationship between economic status and frequency of physical exams may be stronger for seniors and weaker for children and teenagers. In this case, the participant's age is the moderating variable.
These variables are constant during a study and don't affect other variables. Using a control variable can help prevent bias in experiments. For example, suppose you're researching plant development. You may use the same amount of fertilizer and water for each plant, making them control variables of the experiment.
These variables involve numbers or amounts. For example, an individual's height and the distance they walk daily are quantitative variables. Here are the categories of quantitative variables:
Discrete: refers to any numerical variables you can realistically count, such as coins in your wallet or books on a shelf
Continuous: refers to numerical variables you can't completely count, such as hair strands on your hair and time
Related: What Is Quantitative Analysis?
Extraneous variables refer to factors you're not investigating that can potentially affect the outcomes of your research study. For example, suppose you're assessing whether private tutoring or online courses is more effective at improving students' test scores. If you aren't investigating parental support and how it affects the preferred learning method, it may be an extraneous variable. Considering extraneous variables can help you generate more accurate conclusions about the relationship between independent and dependent variables.
A confounding variable refers to a factor you're not actively considering, which can impact both independent and dependent variables. Identifying and including these variables in your experiments can help validate your results. For example, suppose you're studying the relationship between exercise level and body mass index (BMI). In this case, a participant's age can affect their exercise level and BMI. If you're not actively investigating this factor, it becomes a confounding variable.
A composite variable is a combination of two or more variables, called indicators, which have a conceptual or statistical relationship. Creating composite variables can provide more insights than using each indicator. For example, an individual's body mass index (BMI) is a composite variable that typically provides more information than an individual's weight and height.
A qualitative variable has non-numerical values. For example, your eye colour and educational level are qualitative variables. Here are categories of qualitative variables:
Binary: You can organize these variables in two categories, such as red or blue.
Nominal: You can organize these variables in more than two categories that don't have a specific order. For example, housing and computer types are nominal variables.
Ordinal: You can arrange these variables in more than two categories that follow a specific order. For example, employee satisfaction is typically an ordinal variable you can group into "unsatisfied," "neutral," and "satisfied."
Examples of independent and dependent variables in research studies
Review the following examples to help you learn more about independent variables in workplaces:
This example can help you learn more about identifying independent and dependent variables in academic studies:
Educators at Holty Green Institute research the effects of increased study time on students' academic performance. They survey students, inquiring about the hours they study and the grades earned. After compiling the results, the educators discover a direct correlation between the grades earned and the data used for the study. In this case, the students' study hours are independent variables because they don't change with other variables. In comparison, a student's grade is the dependent variable because how many hours a student commits to preparing for a test or exam can affect their grade.
This example can offer insights into distinguishing independent and dependent variables when performing ecological studies:
A government agency is looking to understand a city's traffic patterns and climate change effects. Its researchers conduct a study assessing car usage and air quality. From their results, they discover that a location's air quality doesn't directly affect how many individuals drive vehicles. They also find that increased car usage and traffic can lead to more carbon emissions, reducing the location's air quality. In this case, car usage is an independent variable because it doesn't change with changes in air quality. In comparison, the air quality is the dependent variable because it can change if more individuals use cars.
This example can help you learn more about identifying independent and dependent variables in marketing studies:
To improve future marketing efforts, Evergreen Blue Inc. studies its current campaign's effectiveness with different age groups. Using data from social media platforms, the company's marketers create surveys, send links to them, group respondent ages, and measure the response rate. The results show that the company's current marketing campaign is effective among teenagers. The respondent's age is the independent variable because it doesn't change as the participant clicks on the link. In comparison, the response rate is a dependent variable because it typically depends on a user's age, with more teenagers and children likely to use social media.
This example can offer insights into distinguishing independent and dependent variables in medical studies:
A pharmaceutical company develops a medical treatment and performs clinical trials to determine the medication's effectiveness and possible side effects. The company provides varying dosages to patients with different demographic information. In this example, the dosage and demographic group are independent variables because they don't change with more medications. In comparison, the medication's effectiveness and potential side effects are the dependent variables.
This example can offer insights into distinguishing independent and dependent variables in sociological studies:
Sociologists at Billow Votry study the effect of higher wages in a community. By tracking health factors, homeownership, and economic status, they identify trends within the data set and determine correlations. In this case, the wage level of individuals is the study's independent variable. In comparison, the effect of higher wages is the study's dependent variable.
Now that we've answered the question, "what is an independent variable?" and discussed identifying independent and dependent variables, you'll be better prepared to use them in your own research.
Please note that none of the companies, institutions, or organizations mentioned in this article are affiliated with Indeed.
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