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Alexander Enterprises manufactures plastic parts for the automotive industry. Its sales (in thousands of dollars) for 2012Q1 through 2016Q4 are as follows: Period Sales Mar-12
Alexander Enterprises manufactures plastic parts for the automotive industry. Its sales (in thousands of dollars) for 2012Q1 through 2016Q4 are as follows:
Period | Sales |
Mar-12 | 3,816.5 |
Jun-12 | 3,916.7 |
Sep-12 | 3,978.8 |
Dec-12 | 4,046.6 |
Mar-13 | 4,119.1 |
Jun-13 | 4,169.4 |
Sep-13 | 4,193.0 |
Dec-13 | 4,216.4 |
Mar-14 | 4,238.1 |
Jun-14 | 4,270.5 |
Sep-14 | 4,321.8 |
Dec-14 | 4,349.5 |
Mar-15 | 4,406.4 |
Jun-15 | 4,394.6 |
Sep-15 | 4,422.3 |
Dec-15 | 4,430.8 |
Mar-16 | 4,463.9 |
Jun-16 | 4,517.8 |
Sep-16 | 4,563.6 |
Dec-16 | 4,633.0 |
Mar-17 | |
Jun-17 | |
Sep-17 | |
Dec-17 |
- Begin by preparing a time series plot of the data set. Does it appear from this plot that a linear trend model will be appropriate? Explain.
- Use a bivariate linear regression trend model to estimate this trend equation: SALES = a + b(TIME) Is the sign of b what you would expect? Is b significantly different from zero? What is the coefficient of determination for this model? Explain your answers.
- Based on this model, make a trend forecast of sales (SALESFT) for the four quarters of 2017.
- The actual sales (SALESA) for the four quarters are provided in the table.
2017, Q1 | 4667.1 |
2017, Q2 | 4710.3 |
2017, Q3 | 4738.7 |
2017, Q4 | 4789.0 |
Calculate the MAPE for this forecast model in the historical period (2012, Q1-2016, Q4) as well as for the forecast horizon (2017, Q1-2017, Q4). Which of these measures accuracy and which measures fit?
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