Problem 4 The quarterly sales data of one company over the past three years follow. Year 2019 Qeri Qtr2 Qtra Qtr4 2020 Qtri Qtr2 Qtr3 Qtr4 2021 Qtri Qtr2 Qtr3 Qtr4 Sum of Sales Amount 113788.668 30739.191 30274.866 26493.477 26281.134 118597.092 32277.195 31854.921 27643.779 26821.197 127046.229 33749.148 33255.927 29940.456 30100.698 Hình 1: Data Table for Exercise 4 a. Construct a time series plot. What type of pattern erists in the data? b. Use a regression model with dummy variables to develop an equation to account for seasonal effects (only) in the data. c. Compute the quarterly forecasts for next year. d. Take into account for both the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.

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Problem 4
The quarterly sales data of one company over the past three years follow.
Year
2019
Qtr1
Qtr2
Qtr3
Qtr4
2020
Qtr1
Qtr2
Qtr3
Qtr4
2021
Qtr1
Qtr2
Qtr3
Qtr4
Sum of Sales Amount
113788.668
30739.191
30274.866
26493.477
26281.134
118597.092
32277.195
31854.921
27643.779
26821.197
127046.229
33749.148
33255.927
29940.456
30100.698
Hình 1: Data Table for Exercise 4
a. Construct a time series plot. What type of pattern erists in the data?
b. Use a regression model with dummy variables to develop an equation to account for seasonal
effects (only) in the data.
c. Compute the quarterly forecasts for next year.
d. Take into account for both the seasonal effects in the data and linear trend, compute the quarterly
forecasts for next year.
Transcribed Image Text:Problem 4 The quarterly sales data of one company over the past three years follow. Year 2019 Qtr1 Qtr2 Qtr3 Qtr4 2020 Qtr1 Qtr2 Qtr3 Qtr4 2021 Qtr1 Qtr2 Qtr3 Qtr4 Sum of Sales Amount 113788.668 30739.191 30274.866 26493.477 26281.134 118597.092 32277.195 31854.921 27643.779 26821.197 127046.229 33749.148 33255.927 29940.456 30100.698 Hình 1: Data Table for Exercise 4 a. Construct a time series plot. What type of pattern erists in the data? b. Use a regression model with dummy variables to develop an equation to account for seasonal effects (only) in the data. c. Compute the quarterly forecasts for next year. d. Take into account for both the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.
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