A restaurant manager collected data on the number of customers in a party in the restaurant and the time elapsed until the party left the restaurant. The manager computed a correlation of 0.78 between the two variables. What information does the correlation provide about the relationship between the number of customers in a party at the restaurant and the time elapsed until the party left the restaurant?
A. The relationship is linear because the correlation is positive.
B. The relationship is not linear because the correlation is positive.
C. The parties with a larger number of customers are associated with the longer times elapsed until the party left the restaurant.
D. The parties with a larger number of customers are associated with the shorter times elapsed until the party left the restaurant.
E. There is no relationship between the number of customers in a party at a table in the restaurant and the time required until the party left the restaurant.

The correlation coefficient 0.78 shows that positive association between two variables number of customers and elapsed time until party left restaurant.

The positive association means that as the number of customers in a party increases the elapsed time also increase. So, we can say that the parties with a larger number of customers are associated with the longer times elapsed until the party left the restaurant.

fichoh fichoh · Answer 2 · 2021-10-01T22:07:43+02:00

The value of the correlation Coefficient, R gives the type and strength of the relationship between two variables. Hence, an R value of 0.78 depicts that parties with larger number of customers are associated with longer elapsed time.

Positive values of R values denotes that the relationship between the two variables is positive, hence, increase in variable A will lead to a corresponding increase in variable B and vice versa.

Association between variables could be positive or negative, non-linear or linear

Since, R is ’positive, then larger Number of customers will be associated with larger times elapsed.

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