Introduction to Independent Variables and Dependent Variables

In an experiment, the independent variable is the characteristic that is manipulated by the researcher to gauge the effect of the changes on the dependent variable. 

Note that, it is always the resulting change on the dependent variable that is measured by altering the independent variable. 

For example, you want to determine the effect of exposure to classical music on the test scores in math. 

To see the changes in the test score you divide students into two groups. Students in Group A listened to classical music for an hour every day for two months. Students in Group B were not instructed to listen to classical music. 

After two months students of both groups were given a math test. It was seen that Group A performed better than Group B. 

In the experiment, test score in math exam was the dependent variable and the exposure or lack thereof to classical music was the independent variable. 

In an Experiment, while the most common study has one independent variable and one dependent variable, it is also possible to have a different level of each variable. 

• • As a researcher, you may want to learn how a single Independent Variable can impact two different dependent variables. 

For example, you run an experiment to learn how playing video games impact a teenager’s memory as well as their mood. In the experiment, while playing video games is your independent variable, the teenager’s memory, and mood are your two dependent variables. 

• • Similarly, independent variables can have different levels. In some experiments, you may need to use multiple independent variables to see the various effects they may have on the single dependent variable.

For example, you want to see how a healthy diet can help with weight loss. So, you will look for several types of a healthy diet and their impact on weight. 

In this case, different types of diet would be your different levels of the independent variable, while weight loss is the outcome that makes it the dependent variable. 

• • Applying two levels of IV can tell you if it has any effect on the DV.
  • Applying multiple levels of IV can show you how it influences the outcome of DV. 
  • In some cases of experimental research, it is not possible to change the independent variable. 

For example, you want to see whether age impacts weight gain. 

• • Age is your Independent Variable
  • Weight gain is your Dependent Variable

You cannot control the age of the people you are studying to understand its impact on weight gain. So, you compare the factors that had an effect on weight and the factors that did not. 

Comparing the difference in the other factors you can learn the changes in the weight of a person caused by their age.