What Correlations Indicate
When you explore linear relationships between a pair of quantitative (numerical) variables, X and Y, your basic question is this: As the X variable increases in value, does the Y variable increase with it, does it decrease in value, or does it just basically not react at all? The answer requires the use of graphs as well as the calculation and interpretation of a certain numerical measure of togetherness — correlation.
Sample questions

Which of the following correlations indicates a strong, negative linear relationship between two quantitative variables?
A. –0.2
B. –0.8
C. 0
D. 0.4
E. 0.8
Answer: B. –0.8
Among the choices, only –0.8 indicates a relationship that’s both negative and strong.

Which of the following correlations indicates a weak, positive linear relationship between two quantitative variables?
A. –0.2
B. –0.6
C. 0.2
D. 0.75
E. 0.9
Answer: C. 0.2
Among the choices, only 0.2 indicates a relationship that’s both positive and weak.

Which of the following correlations indicates a very strong, positive linear relationship between two quantitative variables?
A. –0.7
B. –0.1
C. 0.2
D. 0.4
E. 0.9
Answer: E. 0.9
Among the choices, only 0.9 indicates a relationship that’s both positive and very strong.

Which of the following correlations indicates a weak, negative linear relationship between two quantitative variables?
A. –0.2
B. –0.8
C. –1
D. 0.4
E. 0.8
Answer: A. –0.2
Among the choices, only –0.2 indicates a relationship that’s both negative and weak.
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