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The difference between independent and dependent variables is a fundamental concept in statistical analysis and research. An independent variable is a factor that is manipulated or controlled by the researcher, and its values are not affected by any other variables in the study. On the other hand, a dependent variable is a factor whose values are influenced by changes in the independent variable. In other words, the dependent variable is the outcome or response that is being measured, while the independent variable is the cause or predictor of that outcome. Understanding the distinction between these two types of variables is crucial in designing and interpreting scientific studies.
Independent vs. Dependent Variables: What’s the Difference?
In an experiment, there are two main variables:
The independent variable: the variable that an experimenter changes or controls so that they can observe the effects on the dependent variable.
The dependent variable: the variable being measured in an experiment that is “dependent” on the independent variable.
In an experiment, an experimenter is interested in seeing how the dependent variable changes as a result of the independent being changed or manipulated in some way.
Example of an Independent and Dependent Variable
For example, a researcher might change the amount of water they provide to a certain plant to observe how it affects the growth rate of the plant.
In this example, the amount of water given to the plant is controlled by the researcher and, thus, is the independent variable. The growth rate is the dependent variable because it is directly dependent on the amount of water that the plant receives and it’s the variable we’re interested in measuring.
How to Remember the Difference Between Independent and Dependent Variables
An easy way to remember the difference between independent and dependent variables is to insert the two variables into the following sentence in such a way that it makes sense:
Changing (independent variable) affects the value of (dependent variable).
For example, it would make sense to say:
Changing the amount of water affects the value of the plant growth rate.
This is how we know that amount of water is the independent variable and plant growth rate is the dependent variable.
If we tried reversing the positions of these two variables, the sentence wouldn’t make sense:
Changing the plant growth rate affects the value of the amount of water.
More Examples
Here are a few more examples of independent and dependent variables.
Example 1:
A marketer changes the amount of money they spend on advertisements to see how it affects total sales.
Independent variable: amount spent on advertisements
Dependent variable: total sales
Example 2:
A doctor changes the dose of a particular medicine to see how it affects the blood pressure of a patient.
Independent variable: dosage level of medicine
Dependent variable: blood pressure
Example 3:
A researcher changes the version of a study guide given to students to see how it affects exam scores.
Independent variable: the version of the study guide
Dependent variable: exam scores
Independent vs. Dependent Variables on a Graph
When we create a graph, the independent variable will go on the x-axis and the dependent variable will go on the y-axis.
For example, suppose a researcher provides different amounts of water for 20 different plants and measures the growth rate of each plant. The following scatterplot shows the amount of water and the growth rate for each plant:
The independent variable (amount of water) is shown on the x-axis while the dependent variable (growth rate) is shown on the y-axis:
