a. H0: b. Test statistic: Ha: (-0.014-0)/0.0056=-2.5 c. Based on the p-value (0.0198) obtained, what will you conclude in the context of the problem? d. Now, the predictors flyer and display were added to the dataset and a multiple linear regression model was fitted. Part of the R output is shown below- Estimate Standard Error Intercept 81.23 35.24 Price -0.0318 0.023 Flyer 10.21 3.28 Display 21.67 13.27 Adj R Square - 78.8% i. Express the least squares regression model. ii. Interpret the coefficient of Flyer and Display in the context of the problem. iii. Calculate a 95% confidence interval of Flyer and interpret the same in the context of the problem. Can we say that promoting a product through fliers significantly affect its sales? iv. What is the coefficient of multiple determination of this model? Interpret its value. v. Suppose you want to test whether Price has a positive effect on Sales controlling for Flyer and Display. Carry out an appropriate test at a .05 and state your conclusion in the context of the problem. Hypotheses: HO: Ha: Test statistic: Degrees of freedom: Based on the p-value, you would Reject H0 at a 0.01 but not at a=0.05. Reject H0 at a 0.05 and a=1 0.01 but not at a 0.1. Reject H0 at a 0.05 and a = 0.1 but not at a = 0.01. Reject HO at a 0.1 but not at a = 0.01 and a = 0.05. Fail to reject H0 at all the above. a values. .Reject HO at all the above a values.