(f) Use your results from part (a), (b), (d) and (e) to justify why the regression equation you found in part (c) is a good model to describe the relationship between the two variables. (g) Some coaches heard that your group developed a good regression model and would like to make predictions for their athletes in the following situations. When appropriate, provide a prediction. When not appropriate, explain why. (i) A male Canada Games alpine skier who finished a Super G in 73.14 seconds wants to predict his Giant Slalom race time. (ii) A male Canada Games alpine skier who finished a Super G in 52.98 seconds wants to predict his Giant Slalom race time. (iii) A female Canada Games alpine skier who finished a Super G in 56.27 seconds wants to predict her Giant Slalom race time.Question 6 Often, alpine skiers will compete in multiple events in the Canada Winter Games. Male alpine skiers who compete in the Super G and Giant Slalom event want to know if they can use their time from a Super G to predict their time in the forthcoming Giant Slalom. As sample data, we will consider the male alpine skiers who competed in the 2015 Canada Games as given in the Excel sheet Male Super G and Giant Slalom. (a) Construct a scatter plot of the Giant Slalom race time (dependent variable) and Super G race time (independent variable). (b) Find the correlation coefficient. (c) Find the equation of the regression line and add it to the scatter plot. (d) Find the coefficient of determination. (e) Construct a residual plot. (Hint: Using the Analysis ToolPak, go to Data Analysis, choose Regression, and then check the bor beside Residual Plots.)