Consider the following time series. Quarter Year 1 Year 2 Year 3 1 71 68 62 2 49 41 51 3 58 60 53 4 78 81 72 Construct a time series plot. What type of pattern exists in the data? Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1=1 if Quarter 1, 0 otherwise; Qtr2=1 if Quarter 2, 0 otherwise; Qtr3=1 if Quarter 3, 0 otherwise. Compute the quarterly forecast for the next year.
Consider the following time series. Quarter Year 1 Year 2 Year 3 1 71 68 62 2 49 41 51 3 58 60 53 4 78 81 72 Construct a time series plot. What type of pattern exists in the data? Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1=1 if Quarter 1, 0 otherwise; Qtr2=1 if Quarter 2, 0 otherwise; Qtr3=1 if Quarter 3, 0 otherwise. Compute the quarterly forecast for the next year.
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Consider the following time series.
Quarter |
Year 1 |
Year 2 |
Year 3 |
1 |
71 |
68 |
62 |
2 |
49 |
41 |
51 |
3 |
58 |
60 |
53 |
4 |
78 |
81 |
72 |
- Construct a time series plot. What type of pattern exists in the data?
- Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1=1 if Quarter 1, 0 otherwise; Qtr2=1 if Quarter 2, 0 otherwise; Qtr3=1 if Quarter 3, 0 otherwise.
- Compute the quarterly forecast for the next year.
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