The management of the Sunshine Village company compared daily observations of sales revenue and number of ad clicks from the online marketing campaigns. They think that more Ad Clicks translates into more Sales, and they have a strong feeling that Sunshine Village company can increase the revenue by improving CTR (click-through rate).

A group of Humber College students from e-Business Marketing program has been entrusted with the regression analysis. A random sample of 30 daily recordings is shown below. (Sales are in $$thousands.)

\fAdClicks . 500 6E0 700 800 900 1000 1100 I 2[ Sales (a) Check the draft. Select the most appropriate comment. 0 The choice of dependent and independent variables is wrong. The students must have taken AdClicks (not Day#) as the independent variable :3, and Sales should be the dependent variable y. 0 The draft looks incomplete as the students forgot to label the axes. Also, I would probably make the points (Excel markers) bigger. O The roles of the selected variables are mixed up. AdClicks should be the independent variable a), and Sales should be considered as the dependent variable 3;, not the other way around. 0 The choice of dependent and independent variables is correct, but the trend line is missing. 0 None of the above. Please help the Humber College students. Using Excel and 30 daily recordings, please construct a scatter diagram to support or reject the idea of the management. Make sure that you do not repeat the possible mistakes that are described in question 1. Also, please include the regression equation and R2 in the scatter diagram along with the trend line. Based on the result, answer the following questions: (b) The coefficient of determination is R2 = C] The linear correlation coefficient is 'r = C] For part (b), round your answers to 4 decimal places. (c) The regression equation is (do not mix up b3 and b1 ) =+ For part (c), round your answers to 2 decimal places. (d) What percent of the variation in Sales can be explained by the variation in AdClicks? C] % What percent of the variation in Sales cannot be explained by the variation in AdClicks, but is due to other factors? C] % For part (d), express your answers in percent form (i.e. 3.00% instead of 0.03) and round to 2 decimal places. (e) What is the slope of the regression equation? C] For part (e), round your answers to 2 decimal places. (f) How much will the sales revenue amount be expected to change if the number of daily ad clicks increases by one click? Please note that the answer is expected in dollars, not in thousands. | Select an answer v | C] (9) What would be the best predicted sales revenue amount if the number of daily ad clicks is 806? Please note that the answer is expected in dollars, not in thousands. $m (h) Would it be possible to use this regression model to predict the sales revenue amount if the number of daily ad clicks is 217 ? O The forecast would be reliable. Just plug the given number of clicks into the regression equation. 0 The forecast would be reliable, and Sales is approximately 347.24. 0 The forecast would not be reliable, as 217 clicks is not within the sample m-range. O The forecast would be reliable, as the regression equation from question (c) can be used to predict any Sales. 0 None of the above. Do not forget to attach the original Excel file(s)