An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (in millions of dollars) and the resulting percentage increase in sales following the campaign, were presented by the firm. Based on these data, we would compute the least-squares regression line to bey= 6.15 + 0.19x, with x representing campaign cost and y representing the resulting percentage increase in sales. (This line is shown below, along with a scatter plot of the data.)

Campaign Increase in cost, x (in millions of sales, y dollars) (percent) 2.09 6.49 1.65 6.58 2.30 6.69 68 4.07 7.07 2.00 6.77 (percent) Increase in sales, y 3.10 7.00 6.4- 3.21 6.56 3.58 6.84 1.48 6.23 3.88 6.74 2'5 3.02 6.61 Campaign cost, x 1.25 6.33 (in millions of dollars) Send data to calculator V Send data to Excel Based on the sample data and the regression line, complete the following. (a) For these data, values for campaign cost that are less than the mean of the values for campaign cost tend to be paired with values for percentage increase in sales that are (Choose one) V the mean of the values for percentage increase X ? in sales. (b) According to the regression equation, for an increase of one million dollars in advertising campaign cost, there is a corresponding increase of how many percent in sales? (c) From the regression equation, what is the predicted percentage increase in sales when the advertising campaign cost is 4.07 million dollars? (Round your answer to at least two decimal places.) (d) What was the observed percentage increase in sales when the advertising campaign cost was 4.07 million dollars