e)
8.91666667 |
6.91666667 |
7.91666667 |
9.91666667 |
f)
(y - y_d) | (y-y_t) |
1.6666 | 0.041666667 |
1.6666 | 0.041666667 |
1.6666 | 0.041666667 |
1.6666 | 0.041666667 |
0.3334 | 0.333333333 |
0.6666 | 0.666666667 |
0.3334 | 0.333333333 |
0.3334 | 0.333333333 |
1.3334 | 0.291666667 |
2.3334 | 0.708333333 |
1.3334 | 0.291666667 |
1.3334 | 0.291666667 |
1.222233333 | 0.284722222 |
MSE
Model developed in part (b) 1.222233333
Model developed in part (d) 0.284722222
Model in d) is more effective as MSE is less
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(b) Use a multiple regression model with dummy variabies as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if uarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2,0 otherwise; tr3-1 if Quarter 3 0 otherwise. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a sign before the blank. (Example: -300) Value 6.671Qtrit3 Qtr2t2Qtr3t (c) Compute the quarterly...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6 7 2 2 3 6 3 3 5 6 4 5 7 8 (b) Use a multiple 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. If required, round your...
eBook Consider the following time series data. Quarter Year1 Year 2 Year 3 10 10 12 Plot (i) What type of pattern exists in the data? Select your answer b) Use a multi le regression model with dummy variables as ollows to develop an equation to account or seasonal effects in the data tri . 1 if uarter 1 0 otherwise; tr2·1 i uarter 2 0 otherwise; tr3-1 if uarter 3 0 otherwise. If requred, round your answers to three...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 5 8 10 2 1 3 7 3 3 6 8 4 7 10 12 (d) Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part (b) to capture seasonal effects and create a variable t such that t = 1 for Quarter 1 in Year 1, t =...
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Consider the following time series data. Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 6 8 2 2 4 8 3 4 7 9 4 6 9 11 (a) Choose the correct time series plot. (i) (ii) (iii) (iv) - Select your answer -Plot (i)Plot (ii)Plot (iii)Plot (iv)Item 1 What type of pattern exists in the data? - Select your answer -Positive trend pattern, no seasonalityHorizontal pattern, no seasonalityNegative trend pattern, no seasonalityPositive...
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