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(b) Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. (Round your numerical values to three decimal places.) x, - 1 if quarter 1, 0 otherwise; x, = 1 if quarter 2, 0 otherwise; x, = 1 if quarter 3, 0 otherwise 9- 7.667 – 3-xl – 5-x2-4.x3 (c) Compute the quarterly forecasts for the next year based on the model you developed in part (b). (Round your answers to two decimal places.) quarter 1 forecast 4.67 quarter 2 forecast 2.67 quarter 3 forecast 3.67 quarter 4 forecast 7.67 (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 = 2 for quarter 2 in year 1, . t = 12 for quarter 4 in year 3. (Round your numerical values to three decimal places.)

(b) Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. (Round your numerical values to three decimal places.) x, - 1 if quarter 1, 0 otherwise; x, = 1 if quarter 2, 0 otherwise; x, = 1 if quarter 3, 0 otherwise 9- 7.667 – 3-xl – 5-x2-4.x3 (c) Compute the quarterly forecasts for the next year based on the model you developed in part (b). (Round your answers to two decimal places.) quarter 1 forecast 4.67 quarter 2 forecast 2.67 quarter 3 forecast 3.67 quarter 4 forecast 7.67 (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 = 2 for quarter 2 in year 1, . t = 12 for quarter 4 in year 3. (Round your numerical values to three decimal places.)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Please answer part b and d
(b) Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. (Round your numerical values to three decimal places.) X, = 1 if quarter 1, 0 otherwise; x, =1 if quarter 2, 0 otherwise; x, = 1 if quarter 3, 0 otherwise 9 =7.667 – 3.xl – 5-x2 – 4·x3 (c) Compute the quarterly forecasts for the next year based on the model you developed in part (b). (Round your answers to two decimal places.) quarter 1 forecast 4.67 quarter 2 forecast 2.67 quarter 3 forecast 3.67 quarter 4 forecast 7.67 (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 = 2 for quarter 2 in year 1, ..t = 12 for quarter 4 in year 3. (Round your numerical values to three decimal places.) Marc n 3.
Transcribed Image Text:(b) Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. (Round your numerical values to three decimal places.) X, = 1 if quarter 1, 0 otherwise; x, =1 if quarter 2, 0 otherwise; x, = 1 if quarter 3, 0 otherwise 9 =7.667 – 3.xl – 5-x2 – 4·x3 (c) Compute the quarterly forecasts for the next year based on the model you developed in part (b). (Round your answers to two decimal places.) quarter 1 forecast 4.67 quarter 2 forecast 2.67 quarter 3 forecast 3.67 quarter 4 forecast 7.67 (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 = 2 for quarter 2 in year 1, ..t = 12 for quarter 4 in year 3. (Round your numerical values to three decimal places.) Marc n 3.
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 5 1 2 4 6. 8. 4.
Transcribed Image Text:Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 5 1 2 4 6. 8. 4.
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