Independent Variable Definition and Examples

This type of hypothesis is constructed to state the independent variable followed by the predicted impact on the dependent variable. The dependent variable, in both cases, is what is being observed or studied to see how it changes in response to the independent variable. In this particular example, the type of information is the independent variable (because it changes), and the amount of information remembered is the dependent variable (because this is being measured). The dependent variable is the variable being tested and measured in an experiment and is “dependent” on the independent variable. For example, allocating participants to drug or placebo conditions (independent variable) to measure any changes in the intensity of their anxiety (dependent variable).

The subject of confounding and bias relates to a larger discussion of the relationship between correlation and causation. Although two variables may be correlated, this does not imply that there is a causal relationship between them. A researcher wants to determine if the color of an office has any effect on worker productivity. In an experiment, one group of workers performs a task in a yellow room while another performs the same task in a blue room.

• Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page.
• In this particular example, the type of information is the independent variable (because it changes), and the amount of information remembered is the dependent variable (because this is being measured).
• It represents the cause or reason for an outcome.Independent variables are the variables that the experimenter changes to test their dependent variable.
• The results showed that inclusion of the covariate allowed improved estimates of the trend against time to be obtained, compared to analyses which omitted the covariate.
• Each type of diet that the experimenters look at would be a different level of the independent variable while weight loss would always be the dependent variable.

The results showed that inclusion of the covariate allowed improved estimates of the trend against time to be obtained, compared to analyses which omitted the covariate. The independent variables in a particular experiment all depend on the hypothesis and what the experimenters are investigating. Researchers are interested in investigating the effects of the independent variable on other variables, which are known as dependent variables (DV). The independent variable is one that the researchers either manipulate (such as the amount of something) or that already exists but is not dependent upon other variables (such as the age of the participants).

In an experiment on the effects of the type of diet on weight loss, for example, researchers might look at several different types of diet. Each type of diet that the experimenters look at would be a different level of the independent variable while weight loss would always be the dependent variable. For example, in an experiment looking at the effects of studying on test scores, studying would be the independent variable. Researchers are trying to determine if changes to the independent variable (studying) result in significant changes to the dependent variable (the test results). The independent variable (IV) in psychology is the characteristic of an experiment that is manipulated or changed by researchers, not by other variables in the experiment. Researchers must ensure that participants provide informed consent and that their privacy and confidentiality are respected.

Dependent and independent variables

A variable may be thought to alter the dependent or independent variables, but may not actually be the focus of the experiment. So that the variable will be kept constant or monitored to try to minimize its effect on the experiment. Such variables may be designated as either a “controlled variable”, “control variable”, or “fixed variable”. An example is provided by the analysis of trend in sea level by Woodworth (1987). Here the dependent variable (and variable of most interest) was the annual mean sea level at a given location for which a series of yearly values were available. Use was made of a covariate consisting of yearly values of annual mean atmospheric pressure at sea level.

• In other cases, multiple levels of the IV may be used to look at the range of effects that the variable may have.
• Of the two, it is always the dependent variable whose variation is being studied, by altering inputs, also known as regressors in a statistical context.
• Additionally, it is important to avoid manipulating independent variables in ways that could cause harm or discomfort to participants.
• An example of a dependent variable is depression symptoms, which depend on the independent variable (type of therapy).
• The target variable is used in supervised learning algorithms but not in unsupervised learning.

Sometimes varying the independent variables will result in changes in the dependent variables. In other cases, researchers might find that changes in the independent variables have no effect on the variables that are being measured. Independent variables are what we expect will influence dependent variables. A Dependent variable is what happens as a result of the independent variable. For example, if we want to explore whether high concentrations of vehicle exhaust impact incidence of asthma in children, vehicle exhaust is the independent variable while asthma is the dependent variable.

Educators are interested in whether participating in after-school math tutoring can increase scores on standardized math exams. In an experiment, one group of students attends an after-school tutoring session twice a week while another group of students does not receive this additional assistance. In this case, participation in after-school math tutoring is the independent variable. In other cases, multiple levels of the IV may be used to look at the range of effects that the variable may have. Yes, both quantitative and qualitative data can have independent and dependent variables. To ensure cause and effect are established, it is important that we identify exactly how the independent and dependent variables will be measured; this is known as operationalizing the variables.

Examples

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the “Everything Psychology Book.” Ethical guidelines help ensure that research is conducted responsibly and with respect for the well-being of the participants involved. In another example, the hypothesis “Young participants will have significantly better memories than older participants” is not operationalized. “Participants aged between 16 – 30 will recall significantly more nouns from a list of twenty than participants aged between 55 – 70” is operationalized.

A confounding variable in the example of car exhaust and asthma would be differential exposure to other factors that increase respiratory issues, like cigarette smoke or particulates from factories. In this natural experiment, a community living near higher concentrations of car exhaust may also live near factories that pollute or have higher rates of smoking. The independent variable always changes in an experiment, even if there is just a control and an experimental group. The dependent variable may or may not change in response to the independent variable. In the example regarding sleep and student test scores, it’s possible the data might show no change in test scores, no matter how much sleep students get (although this outcome seems unlikely). The point is that a researcher knows the values of the independent variable.

Dependent Variable

For example, in a study examining the effect of post-secondary education on lifetime earnings, some extraneous variables might be gender, ethnicity, social class, genetics, intelligence, age, and so forth. A variable is extraneous only when it can be assumed (or shown) to influence the dependent variable. If it is excluded from the regression and if it has a non-zero covariance with one or more of the independent variables of interest, its omission will bias the regression’s result for the effect of that independent variable of interest. This effect is called confounding or omitted variable bias; in these situations, design changes and/or controlling for a variable statistical control is necessary. Of the two, it is always the dependent variable whose variation is being studied, by altering inputs, also known as regressors in a statistical context. In an experiment, any variable that can be attributed a value without attributing a value to any other variable is called an independent variable.

In an experiment, one group of workers is given a great deal of input in how they perform their work, while the other group is not. The amount of input the workers have over their work is the independent variable in this example. Ethical considerations related to independent and dependent variables involve treating participants fairly and protecting their rights. Variables are given a special name that only applies to experimental investigations. One is called the dependent variable, and the other is the independent variable.

The independent variable is the variable the experimenter manipulates or changes and is assumed to directly affect the dependent variable. These examples are programmatically compiled from various online sources to illustrate current usage of the word ‘independent variable.’ Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Extraneous variables can also include demand characteristics (which are clues about how the participants should respond) and experimenter effects (which is when the researchers accidentally provide clues about how a participant will respond). The role of a variable as independent or dependent can vary depending on the research question and study design. The classification of a variable as independent or dependent depends on how it is used within a specific study. In one study, a variable might be manipulated or controlled to see its effect on another variable, making it independent.

Practice Identifying the Independent Variable

A change in the independent variable directly causes a change in the dependent variable. Although there are many types of bias, two common types are selection bias and information bias. This is because individuals that had a particularly bad (or good) experience with the physician may be more likely to go to the website and provide a rating. Students are often asked to identify the independent and dependent variable in an experiment. It’s even possible for the dependent variable to remain unchanged in response to controlling the independent variable.

If we didn’t do this, then it would be very difficult (if not impossible) to compare the findings of different studies to the same behavior. For example, we might change the type of information (e.g., organized or random) given to participants to see what effect this might have on the amount of information remembered. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page. By Kendra Cherry, MSEd

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the “Everything Psychology Book.” Amanda Tust is a fact-checker, researcher, and writer with a Master of Science in Journalism from Northwestern University’s Medill School of Journalism.

Models and experiments test the effects that the independent variables have on the dependent variables. Sometimes, even if their influence is not of direct interest, independent variables may be included for other reasons, such as to account for their potential confounding effect. A confounding variable, or confounder, affects the relationship between the independent and dependent variables.

It also makes it easier for other researchers to replicate a study and check for reliability. An example of a dependent variable is depression symptoms, which depend on the independent variable (type of therapy). Operational variables (or operationalizing definitions) refer to how you will define and measure a specific variable as it is used in your study.

What are some ethical considerations related to independent and dependent variables?

This enables another psychologist to replicate your research and is essential in establishing reliability (achieving consistency in the results). However, in a different study, that same variable might be the one being measured or observed to understand its relationship with another variable, making it dependent. Researchers should also consider the potential impact of their study on vulnerable populations and ensure that their methods are unbiased and free from discrimination. The key point here is that we have made it absolutely clear what we mean by the terms as they were studied and measured in our experiment.

Examples in Experiments

Remember, the independent variable is the one the experimenter controls to measures its effect on the dependent variable. On the other hand, the scientist has no control on the students’ test scores. In quantitative research, independent variables are usually measured numerically and manipulated to understand their impact on the dependent variable. In qualitative research, independent variables can be qualitative in nature, such as individual experiences, cultural factors, or social contexts, influencing the phenomenon of interest. An independent variable is defines as the variable that is changed or controlled in a scientific experiment. It represents the cause or reason for an outcome.Independent variables are the variables that the experimenter changes to test their dependent variable.

The target variable is used in supervised learning algorithms but not in unsupervised learning. At the outset of an experiment, it is important for researchers to operationally define the independent variable. An operational definition describes exactly what the independent variable is and how it is measured. Doing this helps ensure that the experiments know exactly what they are looking at or manipulating, allowing them to measure it and determine if it is the IV that is causing changes in the DV.