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Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 5 7 2 1 2 5 3 4 6 7 6 8 (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. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. O The time series plot shows a linear trend and no 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 decimal places.) x = 1 if quarter 1, 0 otherwise; x₂-1 if quarter 2, 0 otherwise; xy-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 (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 decimal places.) (e) Compute the quarterly forecasts for the next year based on the model you developed in part (d). (Round your answers to two decimal places.) quarter 1 forecast quarter 2 forecast quarter 3 forecast quarter 4 forecast

Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 5 7 2 1 2 5 3 4 6 7 6 8 (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. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. O The time series plot shows a linear trend and no 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 decimal places.) x = 1 if quarter 1, 0 otherwise; x₂-1 if quarter 2, 0 otherwise; xy-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 (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 decimal places.) (e) Compute the quarterly forecasts for the next year based on the model you developed in part (d). (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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Please solve. Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 5 7 В 2 1 2 5 3 4 6 7 4 6 8 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. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. O The time series plot shows a linear trend and no 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 decimal places.) - 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; x3 = 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 (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 decimal places.) (e) Compute the quarterly forecasts for the next year based on the model you developed in part (d). (Round your answers to two decimal places.) quarter 1 forecast quarter 2 forecast quarter 3 forecast quarter 4 forecast
Transcribed Image Text:Please solve. Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 5 7 В 2 1 2 5 3 4 6 7 4 6 8 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. O The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. O The time series plot shows a linear trend and no 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 decimal places.) - 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; x3 = 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 (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 decimal places.) (e) Compute the quarterly forecasts for the next year based on the model you developed in part (d). (Round your answers to two decimal places.) quarter 1 forecast quarter 2 forecast quarter 3 forecast quarter 4 forecast
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