Multiple Choice
Which of the following best describes a scatterplot and its primary use in statistics?
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11. Correlation
Scatterplots & Intro to Correlation
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Suppose a scatterplot shows a strong positive linear relationship between hours studied and exam scores for a group of students; the best inference that can be made based on the graph is that
A
studying more hours causes higher exam scores for every student
B
there is no relationship between hours studied and exam scores
C
students who study more hours tend to achieve higher exam scores
D
students who study less will always score lower than those who study more
Verified step by step guidance1
Step 1: Understand what a scatterplot with a strong positive linear relationship indicates. It shows that as one variable increases, the other variable tends to increase as well.
Step 2: Recognize that correlation (or association) does not imply causation. Just because two variables move together does not mean one causes the other.
Step 3: Interpret the scatterplot by stating that students who study more hours tend to have higher exam scores, which is a statement about association, not causation.
Step 4: Avoid making absolute claims such as 'studying more hours causes higher scores for every student' or 'students who study less will always score lower,' because individual variation exists and the graph does not prove causality or guarantee outcomes for every individual.
Step 5: Conclude that the best inference from the scatterplot is that there is a positive association: students who study more hours tend to achieve higher exam scores.
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