"Man does not live by a correlation alone." You always need to look at a scatter plot of the data as well. (Neither is foolproof by itself.) You conduct a study to see whether the amount of time spent studying per week is related to GPA for a group of college computer science majors.
Sample questions
How do you designate the "time spent studying" variable on a scatter plot of your data?
Answer: the X variable
The logical assumption in this study is that time spent studying influences grades (GPA), so it makes sense to designate "time spent studying" as the X, or explanatory, variable.
How do you designate the variable "GPA" on a scatter plot of your data?
A. the X variable
B. the Y variable
C. the response variable
D. Choices (A) and (C)
E. Choices (B) and (C)
Answer: E. Choices (B) and (C) (the Y variable; the response variable)
The logical assumption in this study is that time spent studying influences GPA, so it's logical to designate "GPA" as the Y, or response, variable.
How does the correlation change if you switch the measurement of study time from minutes to hours?
Answer: It doesn't change.
The correlation is a unitless measure, so changing the units in which variables are measured won't change their correlation.
How does the correlation change if you switch the designation of the two variables — that is, make the X variable the Y variable and make the Y variable the X variable?
Answer: It doesn't change.
In a correlation, it doesn't matter which variable is designated as X and which as Y; the correlation will be the same either way.
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