The manager of a firm wants to examine the effects of advertising campaigns on the sales of the product. He collects data on advertising expenditure ($000s) and sales revenue ($000s) from 17 stores located in different cities, and estimates the following regression equation:

1. The manager of a firm wants to examine the effects of advertising campaigns on the sales of the product. He collects data on advertising expenditure ($000s) and sales revenue ($000s) from 17 stores located in different cities, and estimates the following regression equation: Salei = Bo + B1 Expenditure; + &; The output when using Excel to estimate the equation is given below: Regression statistics Multiple R 0.98 R square A Adjusted 0.95 R square Standard 73.52 error Observations 15.00 ANOVA df SS MS F Significant F Regression 1.00 1544985.22 1544985.22 285.84 0.00 Residual 13.00 70264.78 5404.98 Total 14.00 1615250.00 Coefficients Standard t Stat P-value Error Intercept -644.95 B -8.85 0.00 Expenditure 195.07 11.54 C 0.00 a. Find the value of A, B, and C, and interpret their meanings. b. Find the simple regression line and interpret the coefficients. c. Can the manager conclude that there is a positive relationship between advertising expenditure and sales at the 1% significance level? d. The manager concludes that the advertising campaigns have been successful because higher advertising expenditure caused higher sales. Why might the manager be wrong