Question 1: A marketing professor is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 125 students who took the course last semester are provided in the file MktHrsPts.xlsx. Using a random sample of 100 students from this data set (using a random seed of 2001}: a. Develop an estimated regression equation showing how total points earned is related to hours spent studying. What is the estimated regression model? b. Test whether each of the regression parameters (5'0 and )3] is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? c. How much of the variation in the sample values of total point earned does the model you estimated in part a explain? d. Mark Sweeney spent 95 hours studying. Use the regression model you estimated in part a to predict the total points Mark earned. Question 2: FBStyles, Inc. sells cosmetic products in the US. The marketing department of FBStyles, Inc. claims that there exits a positive linear relationship between the advertising expenditures and the cosmetics sales. The marketing department recently analyzed the sales of FBStyles' products over a period of 42 weeks. For each week in the sample, FBStyles' sales (SALES) and their advertising expenditures (ADVERT) were recorded. A simple regression analysis was made using this data and the model: SALES = [30 + [31 ADVERT + s The resulting JMP IN output is given below. Note that some parts of the output are deleted on purpose and some of the results are left as"?". Response (Dependent variable): SALES Parameter Estimates Term Estimate Std Error t Ratio lntprcpnt 483,409 157,179