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Following time senes data Pated quarter Year 1 Year 3 Year 3 7. 4 4. (a) Construct a time series plot. What type of pattern exists in the data O The time sertes plot showws a inear trend and ne seasonal pattern in the data The time senes plot shows a linear trend and a seasonal pattern in the data The time sertes plot shows a hortontal pattern, but there is alse a seasonal pattern in the tata O The time senes plot shows a horizontal pattern and ne seasonal pattern in the data (b) Use a multiple regressian madel with dummy variables as foitows to eeveleo an euation te acceut for sesonal ffects in the data. (Rand your numencal values to three decimal places) -quarter 1, 0 otherwise; , if quarter 2,0 otherwise, , Quarter 3, 0 otherwise (c) Compute the quarterly forecasts for the next year based on the model you developed in part (b). (Round yeur answers to twe decimal places) quarter 1 forecast quarter 2 forecast quarter 3 forecast quarter 4 forecast

Following time senes data Pated quarter Year 1 Year 3 Year 3 7. 4 4. (a) Construct a time series plot. What type of pattern exists in the data O The time sertes plot showws a inear trend and ne seasonal pattern in the data The time senes plot shows a linear trend and a seasonal pattern in the data The time sertes plot shows a hortontal pattern, but there is alse a seasonal pattern in the tata O The time senes plot shows a horizontal pattern and ne seasonal pattern in the data (b) Use a multiple regressian madel with dummy variables as foitows to eeveleo an euation te acceut for sesonal ffects in the data. (Rand your numencal values to three decimal places) -quarter 1, 0 otherwise; , if quarter 2,0 otherwise, , Quarter 3, 0 otherwise (c) Compute the quarterly forecasts for the next year based on the model you developed in part (b). (Round yeur answers to twe 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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(d) Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data Ue the dummy veriables you develped in part () t cepture seasoral effects and create a variable t such that t-i for quarter 1 in year 1, -2 for quarter 2 in year 1,t12 rqarter 4yar1nd your numeric vels t thee deome piaces (e) Compute the quarterty forecasts for the next year based on the model you developed in part (a). (Round your answers to twe decimal places quarter 1 forecast quarter 2 forecast quarter 3 forecast quarter 4 forecast O Is the model you developed in part (b) or the model you developed in part (d) more tective ustity your answe O The model in part (b) appears to be more effective since there is no linear trend visibie in the data O The model in part (b) appears to be more effective since it has a higher MSE than the model in part (d) O The model in part (d) appears to be mere effective since it has a lower MSE than the model in part (b). O The model in part (b) appears to be more effective since it has a lower MSE than the model in part (d). O The model in part (d) appears to be more effective since it has more variables then the madel in part (b).
Transcribed Image Text:(d) Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data Ue the dummy veriables you develped in part () t cepture seasoral effects and create a variable t such that t-i for quarter 1 in year 1, -2 for quarter 2 in year 1,t12 rqarter 4yar1nd your numeric vels t thee deome piaces (e) Compute the quarterty forecasts for the next year based on the model you developed in part (a). (Round your answers to twe decimal places quarter 1 forecast quarter 2 forecast quarter 3 forecast quarter 4 forecast O Is the model you developed in part (b) or the model you developed in part (d) more tective ustity your answe O The model in part (b) appears to be more effective since there is no linear trend visibie in the data O The model in part (b) appears to be more effective since it has a higher MSE than the model in part (d) O The model in part (d) appears to be mere effective since it has a lower MSE than the model in part (b). O The model in part (b) appears to be more effective since it has a lower MSE than the model in part (d). O The model in part (d) appears to be more effective since it has more variables then the madel in part (b).
Censider the following time series data giaoaverqueston47e09s6.2 Pasted pdale Quarter Year 1 Year 2 Year 3 2. 3. (a) Construct a time series plot. What type of pattern eists in the data? O The time series plot shows a inear trend and ne seasonal pattern in the data O The time series plot shows a inear trend and a seasonal pattern in the data O The time series plot shows a horizontal pattern, but there is alse a seasonal pattern in the data O The time senes plot shows a horizontal pattern and no seasonal pattern in the data (b) Use a multiple regression model with dummy variables as foilows to develep an equation te account for seasonal effects in the data. (Rund vour numencal values to three decimal places) *-1r quarter 1, o otherwise; x,-1if quarter 2. 0 otherwise: 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:Censider the following time series data giaoaverqueston47e09s6.2 Pasted pdale Quarter Year 1 Year 2 Year 3 2. 3. (a) Construct a time series plot. What type of pattern eists in the data? O The time series plot shows a inear trend and ne seasonal pattern in the data O The time series plot shows a inear trend and a seasonal pattern in the data O The time series plot shows a horizontal pattern, but there is alse a seasonal pattern in the data O The time senes plot shows a horizontal pattern and no seasonal pattern in the data (b) Use a multiple regression model with dummy variables as foilows to develep an equation te account for seasonal effects in the data. (Rund vour numencal values to three decimal places) *-1r quarter 1, o otherwise; x,-1if quarter 2. 0 otherwise: 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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