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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 de x₁1 if quarter 1, 0 otherwise; x₂1 f quarter 2, 0 otherwise; x 1 if quarter 3, 0 otherwise 9₁- (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 Quarter 2 forecast quarter 3 forecast quarter 4 forecast

(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 de x₁1 if quarter 1, 0 otherwise; x₂1 f quarter 2, 0 otherwise; x 1 if quarter 3, 0 otherwise 9₁- (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 Quarter 2 forecast quarter 3 forecast quarter 4 forecast

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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Consider the following time series data. Quarter Year 1 1 2 9- 3 4 3 1 2 6 Year 2 Year 3 5 2 4 8 6 5 5 9 (a) Construct a time series plot. What type of pattern exists in the data? O The time series plot shows a horizontal pattern and no seasonal pattern in the data. The time series plot shows a linear trend and a seasonal pattern in the data. The time series plot shows a linear trend and no seasonal pattern in the data. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. (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 decima X-1 if quarter 1, 0 otherwise; x 1 if quarter 2, 0 otherwise; x, 1 if quarter 3, 0 otherwise (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 quarter 2 forecast quarter 3 forecast quarter 4 forecast
Transcribed Image Text:Consider the following time series data. Quarter Year 1 1 2 9- 3 4 3 1 2 6 Year 2 Year 3 5 2 4 8 6 5 5 9 (a) Construct a time series plot. What type of pattern exists in the data? O The time series plot shows a horizontal pattern and no seasonal pattern in the data. The time series plot shows a linear trend and a seasonal pattern in the data. The time series plot shows a linear trend and no seasonal pattern in the data. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. (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 decima X-1 if quarter 1, 0 otherwise; x 1 if quarter 2, 0 otherwise; x, 1 if quarter 3, 0 otherwise (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 quarter 2 forecast quarter 3 forecast quarter 4 forecast
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