Required information [The following information applies to the questions displayed below.] Lexon Inc. is a large manufacturer of affordable DVD players. Management recently became aware of rising expenses resulting from returns of malfunctioning products. As a starting point for further analysis, Paige Jennings, the controller, wants to test different forecasting methods and then use the best one to forecast quarterly expenses for 2019. The relevant quarterly data for the previous three years follow: 2016 Quarter 1 2 3 4 Return Expenses $ 13,900 12, 600 12, 900 15, 200 2017 Quarter 1 2 3 4 Return Expenses $ 14, 300 13, 400 13,000 15, 600 2018 Quarter 1 2 3 4 Return Expenses $ 14, 800 13, 700 13,500 16, 300 The result of a simple regression analysis using all 12 data points yielded an intercept of $13,154.55 and a coefficient for the independent variable of $145.45. (R-squared = 0.20, SE = $1,084.18.) 2. Looking at the graph you prepared for requirement 1, select two representative data points and calculate the quarterly forecast for 2019 using the high-low method. 3. Calculate the quarterly forecasts for 2019 using the results of a regression analysis. Evaluate the results of the regression analysis and make appropriate changes to improve the model. Required 2 Required 3 Calculate the quarterly forecasts for 2019 using the results of a regression analysis. Evaluate the results of the regression analysis and make appropriate changes to improve the model. (Do not round intermediate calculations. Round your final answers to two decimal places.) Regression One 2019 Predicted Quarter Expenses 1 $ 15,045.40 X 2 $ 15,190.85 X 3 $ 15,336.30 X 4 $ 15,481.75 X Regression Two 2019 Predicted Quarter Expenses 1 2 3 4 Required information [The following information applies to the questions displayed below.] Lexon Inc. is a large manufacturer of affordable DVD players. Management recently became aware of rising expenses resulting from returns of malfunctioning products. As a starting point for further analysis, Paige Jennings, the controller, wants to test different forecasting methods and then use the best one to forecast quarterly expenses for 2019. The relevant quarterly data for the previous three years follow: 2016 Quarter 1 2 3 4 Return Expenses $ 13,900 12, 600 12, 900 15, 200 2017 Quarter 1 2 3 4 Return Expenses $ 14, 300 13, 400 13,000 15, 600 2018 Quarter 1 2 3 4 Return Expenses $ 14, 800 13, 700 13,500 16, 300 The result of a simple regression analysis using all 12 data points yielded an intercept of $13,154.55 and a coefficient for the independent variable of $145.45. (R-squared = 0.20, SE = $1,084.18.) 2. Looking at the graph you prepared for requirement 1, select two representative data points and calculate the quarterly forecast for 2019 using the high-low method. 3. Calculate the quarterly forecasts for 2019 using the results of a regression analysis. Evaluate the results of the regression analysis and make appropriate changes to improve the model. Required 2 Required 3 Calculate the quarterly forecasts for 2019 using the results of a regression analysis. Evaluate the results of the regression analysis and make appropriate changes to improve the model. (Do not round intermediate calculations. Round your final answers to two decimal places.) Regression One 2019 Predicted Quarter Expenses 1 $ 15,045.40 X 2 $ 15,190.85 X 3 $ 15,336.30 X 4 $ 15,481.75 X Regression Two 2019 Predicted Quarter Expenses 1 2 3 4
