The following data were collected on the study of the relationship between a company’s retail sales and advertising dollars:

The following data were collected on the study of the relationship between a company’s retail sales and advertising dollars:

Retail Sales ($) Advertising ($)

31,457 16,136

37,031 17,809

40,543 19,848

43,375 23,770

47,594 25,075

51,160 27,911

52,807 32,947

55,796 34,906

57,885 35,367

59,416 38,880

a. Obtain a linear regression line for the data. (Round your answer to 2 decimal places, the tolerance is +/-0.01.)

b. Compute a correlation coefficient and determine the strength of the linear relationship. (Round your answer to 2 decimal places, the tolerance is +/-0.01.)

c. Using the linear regression equation, develop a forecast of retail sales for advertising dollars of $42,626. (Round your answer to 2 decimal places, the tolerance is +/-0.01. Do not round intermediate results used to achieve this answer.)

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The following data were collected on the study of the relationship between a company’s retail sales and advertising dollars:

The following data were collected on the study of the relationship between a company’s retail sales and advertising dollars:

Retail Sales ($) Advertising ($)

31,457 16,136

37,031 17,809

40,543 19,848

43,375 23,770

47,594 25,075

51,160 27,911

52,807 32,947

55,796 34,906

57,885 35,367

59,416 38,880

a. Obtain a linear regression line for the data. (Round your answer to 2 decimal places, the tolerance is +/-0.01.)

b. Compute a correlation coefficient and determine the strength of the linear relationship. (Round your answer to 2 decimal places, the tolerance is +/-0.01.)

c. Using the linear regression equation, develop a forecast of retail sales for advertising dollars of $42,626. (Round your answer to 2 decimal places, the tolerance is +/-0.01. Do not round intermediate results used to achieve this answer.)

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