3) Consider the following time series. Year 1 71 49 58 78 Quarter 1 2 3 4 Year 2 68 41 60 81 Year 3 62 51 53 72 a) Construct a time series plot. What type of pattern exists in the data? b) Use a multiple linear 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. c) Compute the quarterly forecast for the next year.
3) Consider the following time series. Year 1 71 49 58 78 Quarter 1 2 3 4 Year 2 68 41 60 81 Year 3 62 51 53 72 a) Construct a time series plot. What type of pattern exists in the data? b) Use a multiple linear 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. c) Compute the quarterly forecast for the next year.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.CR: Chapter 1 Review
Problem 86CR
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3) Consider the following time series.
Year 1
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Year 2
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60
81
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1
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Year 3
62
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a) Construct a time series plot. What type of pattern exists in the data?
b) Use a multiple linear 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.
c) Compute the quarterly forecast for the next year.
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