1.1.2 - Explanatory & Response Variables
In some research studies one variable is used to predict or explain differences in another variable. In those cases, the explanatory variable is used to predict or explain differences in the response variable. In an experimental study, the explanatory variable is the variable that is manipulated by the researcher.
- Explanatory Variable
Also known as the independent or predictor variable, it explains variations in the response variable; in an experimental study, it is manipulated by the researcher
- Response Variable
Also known as the dependent or outcome variable, its value is predicted or its variation is explained by the explanatory variable; in an experimental study, this is the outcome that is measured following manipulation of the explanatory variable
Example: Panda Fertility Treatments Section
A team of veterinarians wants to compare the effectiveness of two fertility treatments for pandas in captivity. The two treatments are in-vitro fertilization and male fertility medications. This experiment has one explanatory variable: type of fertility treatment. The response variable is a measure of fertility rate.
Example: Public Speaking Approaches Section
A public speaking teacher has developed a new lesson that she believes decreases student anxiety in public speaking situations more than the old lesson. She designs an experiment to test if her new lesson works better than the old lesson. Public speaking students are randomly assigned to receive either the new or old lesson; their anxiety levels during a variety of public speaking experiences are measured. This experiment has one explanatory variable: the lesson received. The response variable is anxiety level.
Example: Coffee Bean Origin Section
A researcher believes that the origin of the beans used to make a cup of coffee affects hyperactivity. He wants to compare coffee from three different regions: Africa, South America, and Mexico. The explanatory variable is the origin of coffee bean; this has three levels: Africa, South America, and Mexico. The response variable is hyperactivity level.
Example: Height & Age Section
A group of middle school students wants to know if they can use height to predict age. They take a random sample of 50 people at their school, both students and teachers, and record each individual's height and age. This is an observational study. The students want to use height to predict age so the explanatory variable is height and the response variable is age.
Example: Gender & Height Section
Research question: Do third grade boys tend to be taller than third grade girls?
This is an observational study. The researcher wants to use gender to explain differences in height. The explanatory variable is gender. The response variable is height.