The Helicopter Division of Aerospatiale is studying assembly costs at its Marseilles plant. Past data indicates the accompanying data of number of labor hours per helicopter. Reduction in labor hours over time is often called a "learning curve" phenomenon. Using these data, apply simple linear regression and examine the residual plot. What do you conclude? Construct a scatter chart and use the Excel Trendline feature to identify the best type of curvilinear trendline (but not going beyond a second-order polynomial) that maximizes R. Click the icon to view the Helicopter Data. The residuals plot has a nonlinear shape. Therefore, this data cannot be modeled with a linear model. Determine the best curvilinear trendline that maximizes R2. Data table for number of hours per helicopter - X OA. T The best trendline is Logarithmic with an R value of . The equation is y = ( ) In (x) + (Round the coefficient of the logarithm to one decimal place as needed. Round all other values to three decimal places as needed.) Helicopter Number Labor Hours O B. The best trendline is Power with an R value of . The equation is y = ( x 2000 1500 (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) 1237 O C. The best trendline is Polynomial with an R value of . The equation is y = ( )x2 +x+. 1 145 CO NOMIAWN- 1071 (Round to three decimal places as needed.) 1028 OD. 984 The best trendline is Exponential with an R value of . The equation is y = ( ) e 955 (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) Print Done