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Quarterly Sales of a Department Store for the Last Seven

Question 54

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Quarterly sales of a department store for the last seven years are given in the following table. Quarterly sales of a department store for the last seven years are given in the following table. The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β<sub>0</sub> + β<sub>1</sub>Qtr1 + β<sub>2</sub>Qtr2 + β<sub>3</sub>Qtr3 + β<sub>4</sub>t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation with = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended? Quarterly sales of a department store for the last seven years are given in the following table. The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β<sub>0</sub> + β<sub>1</sub>Qtr1 + β<sub>2</sub>Qtr2 + β<sub>3</sub>Qtr3 + β<sub>4</sub>t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation with = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended? The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β0 + β1Qtr1 + β2Qtr2 + β3Qtr3 + β4t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. Quarterly sales of a department store for the last seven years are given in the following table. The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β<sub>0</sub> + β<sub>1</sub>Qtr1 + β<sub>2</sub>Qtr2 + β<sub>3</sub>Qtr3 + β<sub>4</sub>t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation with = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended? (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, Quarterly sales of a department store for the last seven years are given in the following table. The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β<sub>0</sub> + β<sub>1</sub>Qtr1 + β<sub>2</sub>Qtr2 + β<sub>3</sub>Qtr3 + β<sub>4</sub>t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation with = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended? = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation Quarterly sales of a department store for the last seven years are given in the following table. The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β<sub>0</sub> + β<sub>1</sub>Qtr1 + β<sub>2</sub>Qtr2 + β<sub>3</sub>Qtr3 + β<sub>4</sub>t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation with = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended? with Quarterly sales of a department store for the last seven years are given in the following table. The Excel scatterplot shown indicates that the quarterly sales have an increasing trend and seasonality.Therefore,the linear regression model,Sales = β<sub>0</sub> + β<sub>1</sub>Qtr1 + β<sub>2</sub>Qtr2 + β<sub>3</sub>Qtr3 + β<sub>4</sub>t + ε,with three seasonal dummy variables Qtr1,Qtr2,and Qtr3,and the decomposition method are proposed to make sales forecasts.For the regression model,the following Excel partial output is available. (Use Excel. )Using MSE and MAD,compare the linear trend equation with seasonal dummy variables, = 31,9261 - 7.855Qtr1 - 4.7362Qtr2 - 7.1656Qtr3 + 1.0749t,and the decomposition method equation with = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended? = 26.8819 + 1.0780t and the quarterly seasonal indices: 0.9322,1.0066,0.9441,and 1.1171.Which of the two corresponding forecasting models is recommended?

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