I can't figure out regression one and regression two predicted expenses. can you please help me.
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 2017 Quarter Quarter Return Expenses $ 14,100 12,700 13,000 Return Expenses $ 14,500 13,600 13,209 15,809 Return Expenses $ 15,000 13,900 13,700 16,589 The result of a simple regression analysis using all 12 data points yielded an intercept of $13,301.52 and a coefficient for the independent variable of $151.05. (R-squared=0.46, SE = $1,098.82.) Required: Plot the data in the order of the dates. (To earn full credit for this graph you must plot all required points for each curve. While plotting the points a tool icon will pop up. You can use this to enter exact co-ordinates for your points as needed.) Return Expense 17,000 16,000 15,000 14,000 13,000 12,000 11,000 2016 Quarter 2017 Quarter 2 018 Quarter Return Expenses $. 14,100 12,700 13,000 15,480 Return Expenses 14,500 13,608 13, 200 15,800 Return Expenses $ 15,888 13,988 13,700 16,500 The result of a simple regression analysis using all 12 data points yielded an intercept of $13,301.52 and a coefficient for the independent variable of $151.05. (R-squared=0.46, SE = $1,098.82.) 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 Answer is not complete. Complete this question by entering your answers in the tabs below. Required 2. Required 3 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 2019 Quarter 1 5 2 Return Expenses 16,880 17.260 17,640 18,020 Required 3 > The result of a simple regression analysis using all 12 data points yielded an intercept of $13,301.52 and a coefficient for the independent variable of $15105. (R-squared = 0.46, SE = $1.098.82) 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. Complete this question by entering your answers in the tabs below. 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. (Round your answers to 2 decimal places for Regression One.) Regression One Predicted 2019 Quarter Expenses Regression Two Predicted 2019 Quarter Expenses Nex 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 2017 Quarter Quarter Return Expenses $ 14,100 12,700 13,000 Return Expenses $ 14,500 13,600 13,209 15,809 Return Expenses $ 15,000 13,900 13,700 16,589 The result of a simple regression analysis using all 12 data points yielded an intercept of $13,301.52 and a coefficient for the independent variable of $151.05. (R-squared=0.46, SE = $1,098.82.) Required: Plot the data in the order of the dates. (To earn full credit for this graph you must plot all required points for each curve. While plotting the points a tool icon will pop up. You can use this to enter exact co-ordinates for your points as needed.) Return Expense 17,000 16,000 15,000 14,000 13,000 12,000 11,000 2016 Quarter 2017 Quarter 2 018 Quarter Return Expenses $. 14,100 12,700 13,000 15,480 Return Expenses 14,500 13,608 13, 200 15,800 Return Expenses $ 15,888 13,988 13,700 16,500 The result of a simple regression analysis using all 12 data points yielded an intercept of $13,301.52 and a coefficient for the independent variable of $151.05. (R-squared=0.46, SE = $1,098.82.) 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 Answer is not complete. Complete this question by entering your answers in the tabs below. Required 2. Required 3 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 2019 Quarter 1 5 2 Return Expenses 16,880 17.260 17,640 18,020 Required 3 > The result of a simple regression analysis using all 12 data points yielded an intercept of $13,301.52 and a coefficient for the independent variable of $15105. (R-squared = 0.46, SE = $1.098.82) 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. Complete this question by entering your answers in the tabs below. 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. (Round your answers to 2 decimal places for Regression One.) Regression One Predicted 2019 Quarter Expenses Regression Two Predicted 2019 Quarter Expenses Nex
