Table of Contents
- Variables in Research
- Dependent Variables in Research
- Independent Variables in Research
- Comparing Dependent and Independent Variables
- Other Types of Variables in Research
- Lesson Summary
The definition of a variable in the context of a research study is some feature with the potential to change, typically one that may influence or reflect a relationship or outcome. For example, potential variables might be time it takes for something to occur, whether or not an object is used within a study, or the presence of a feature among members of the sample.
Within research, independent and dependent variables are key, forming the basis on which a study is performed. However, other types of variables may come into play within a study, such as confounding variables, controlled variables, extraneous, and moderator variables.
A dependent variable is one being measured in an experiment, reflecting an outcome. Researchers do not directly control this variable. Instead, they hope to learn something about the relationship between different variables by observing how the dependent variable reacts under different circumstances.
Although "dependent variable" is the most commonly used term, they may also be referred to as response variables, outcome variable, or left-hand-side variable. These alternate names help to further illustrate their purpose: a dependent variable shows a response to changes in other variables, displaying the outcome.
The meaning of "left-hand-side" is less immediately transparent, but becomes more obvious when considering the format of a basic algebraic equation. Typically, the dependent variable in these is referred to as "Y" and placed on the left-hand-side of the equation. Because of this standard, dependent variables may also be called the Y variable as well, and the dependent variable is usually seen on the y-axis in graphs.
One example of a dependent variable would be a student's test scores. Several factors would influence these scores, such as the amount of time spent studying, amount of sleep, or the stress levels of the student. Ultimately, the dependent variable is not static or controlled directly, but is subject to change depending on the independent variables involved.
An independent variable is one that the researcher controls or otherwise manipulates within a study. In order to determine the relationship between dependent and independent variables, a researcher will purposefully change an independent variable, watching to see if and how the dependent variable changes in response.
The independent variable can alternately be called the explanatory, predicator, right-hand-side, or X variable. Similarly to dependent variables, these reflect the uses of independent variables, as they are intended to explain or predict changes in the dependent variables. Likewise, independent variables are often referred to as "X" in basic algebraic equations and plotted using the x-axis. In research, the experimenters will generally control independent variables as much as possible, so that they can understand their true relationship with the dependent variables.
For example, a research study might use age as an independent variable, since it influences some potential dependent variables. Obviously, a researcher cannot randomly assign ages to participants, but they could only allow participants of certain ages into a study or sort a sample into desired age groups.
|Research Topic||Independent Variable||Dependent Variable|
|All Research Topics||Manipulated by the researcher.||Measured by the researcher.|
|All Research Topics||What is being changed.||What is changing in response.|
|Plants grow faster in warmer temperatures.||Temperature||Plant Growth|
|To what extent does traffic affect a person's mood?||Traffic||Mood|
|People walk slower after drinking coffee.||Drinking Coffee||Walking Speed|
Many research studies have independent and dependent variables, since understanding cause-and-effect between them is a key end goal. Some examples of research questions involving these variables include:
While the independent and dependent variables are the most commonly discussed variables in research, other variables can influence outcomes. These include confounding, extraneous, control, and moderator variables.
A confounding variable, also known as a "third variable," changes the dependent variable despite not being the independent variable being studied. This can cause issues within a study. After all, since variation in a confounding variable causes a response in a dependent variable, that response may be misattributed the independent variable. In order to ensure that the observed outcome is only due to changes in independent variables, it is crucial to determine what confounding variables might sway experimental results.
Identifying the confounding variable(s) and handling them helps to ensure that the relationship being observed between independent and dependent variables is real, and that the results of a study are valid. Validity refers to the closeness of results between repeated experiments. If another researcher were to repeat the initial experiment, they may or may not obtain the same (or similar) results.
A common example is the correlation between ice cream sales and crime rates. Since both go up at the same time, it might be easy for a researcher to assume that a relationship exists between the two: perhaps eating ice cream causes crime, or there's some other nefarious connection between the two. However, the real cause is a confounding variable, temperature. Ice cream sales go up when it is hot outside, and so does crime.
An extraneous variable is any variable present within the experiment that might make the relationship between the independent and dependent variables weaker than initially predicted or observed. There are several kinds of extraneous variables that may be found within a research experiment. Some examples include:
One example is that if you wanted to see whether the amount of time studying (independent variable) impacts the test score (dependent variable), you would also need to account for the time spent sleeping prior to the exam, the temperature of the exam room, and many other factors that may influence the test score (extraneous variables).
A control variable is something the researcher manipulates in order to keep it constant between conditions, allowing the results to be more homogeneous and/or valid by preventing it from becoming confounding. For example, in an experiment about the effect of temperature on plant growth, researchers would want to keep variables such as the amount of water and soil type the same for every plant in the experiment. Otherwise, these variables would influence growth, becoming confounding variables.
A moderator variable changes how much the independent variable influences on the dependent variable, moderating the strength of the relationship between the two variables. When comparing test scores based on amount of hours spent studying studying, a potential moderator variable could be the health of the student taking the exam. Moderator variables could be anything pertaining to a person's categorical variables (age, ethnicity, sexual orientation, health status) or quantitative variables (age, weight, height).
A variable is some aspect of an experiment that can be subject to change, which a researcher typically manipulate and/or measures. The two main variables within a study are the independent variable, which is the variable that is manipulated by the experimenter, and the dependent variable, which is the variable that indirectly changes due to the manipulation in the independent variable. The independent variable is sometimes denoted as 'x', and the dependent as 'y', since they are usually shown on the x-axis and the y-axis respectively.
Other kinds of variables exist as well. Confounding variables act as the "third" variable in the independent and dependent variable relationship, acting as an influencer that may have not been accounted for. Extraneous variables are any and all factors that may contribute to the effect seen in the dependent variable, including demand characteristics, experimenter effect, or situational variables. Control and moderator variables are respectively potential confounders that are kept constant for all participants, and variables that may affect the strength of the relationship between the independent and dependent variables, such as weight, height, ethnicity, or health status.
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The dependent variable in a research study or experiment is what is being measured in the study or experiment.
The independent variable in a research study or experiment is what the researcher is changing in the study or experiment. It is the variable that is being manipulated.
The independent variable is responsible for changing the dependent variable.
A variable is something that can be measured in a study or experiment. The independent and dependent variable are vital to the understanding and development of research.
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