A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square feet. A random sample of 21 stores was selected and the store size and average monthly sales were computed. The following results are shown
Store Size (Sq. Ft)Average Monthly Sales
17400……………………………..$581,241.00
15920……………………………..$538,275.00
17440……………………………..$636,059.00
17320……………………………..$574,477.00
15760……………………………..$558,043.00
20200……………………………..$689,256.00
15280……………………………..$552,569.00
17000……………………………..$584,737.00
11920……………………………..$470,551.00
12400……………………………..$520,798.00
15640……………………………..$619,703.00
12560……………………………..$465,416.00
21680……………………………..$730,863.00
14120……………………………..$501,501.00
16680……………………………..$624,255.00
14920……………………………..$567,043.00
18360……………………………..$612,974.00
18440……………………………..$618,122.00
16720……………………………..$691,403.00
19880……………………………..$719,275.00
17880……………………………..$536,592.00
a. Construct a scatter plot using this data. What, if any relationship, appears to exist between the two variables?
b. Calculate the sample correlation coefficient between store size and average monthly sales.
c. Conduct a hypothesis test to determine if a positive correlation exists between store size and average monthly sales. Use a level of significance of 0.025.