Question

the scatter plot shows the relationship between daily high temperatures in two cities. the linear correlation coefficient for this data is r = 0.993. which statement is the best interpretation of the linear correlation coefficient for the data? a. the correlation coefficient indicates no relationship between temperatures in the two cities. b. the correlation coefficient indicates very little correlation between the temperatures in the two cities. c. the correlation coefficient indicates weak support of the claim that as the temperature rises in one city it will rise in the other city. d. the correlation coefficient indicates strong support of the claim that as the temperature rises in one city it will rise in the other city.

Explanation:

The linear correlation coefficient $r$ ranges from - 1 to 1. A value close to 1 indicates a strong positive linear relationship, a value close to -1 indicates a strong negative linear relationship, and a value close to 0 indicates little to no linear relationship. Here, $r = 0.993$ which is very close to 1, meaning as one variable (temperature in one city) increases, the other variable (temperature in the other city) also tends to increase.

Answer:

D. The correlation coefficient indicates strong support of the claim that as the temperature rises in one city it will rise in the other city.