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RUHungry Banquet Hall – Guests Served by quarter since January 2017.
|
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Quarter |
Period # |
Guests Served |
|
2017 |
1 |
1 |
3,500 |
|
2 |
2 |
8,300 |
|
|
3 |
3 |
5,400 |
|
|
4 |
4 |
9,050 |
|
|
2018 |
1 |
5 |
4,300 |
|
2 |
6 |
5,800 |
|
|
3 |
7 |
3,300 |
|
|
4 |
8 |
5,800 |
|
|
2019 |
1 |
9 |
5,200 |
|
2 |
10 |
9,300 |
|
|
3 |
11 |
7,700 |
|
|
4 |
12 |
15,300 |
|
|
2020 |
1 |
13 |
13,500 |
|
2 |
14 |
17,500 |
|
|
3 |
15 |
12,800 |
|
|
4 |
16 |
18,300 |
|
|
2021 |
1 |
17 |
13,600 |
|
2022 |
2 3 4 1 |
18 19 20 21 |
16,282 17,054 17,826 18,599 |
The RU Hungry demand data displays patterns and you are curious to know if you can improve upon the accuracy of your linear regression forecast. Does applying a seasonality adjustment to your linear regression forecast result in less forecast error?
Using Excel, calculate and apply appropriate adjusting factors for the demand data set provided. Compare the forecast errors of your linear regression forecast with your seasonally adjusted forecast. Once you have completed your analysis of your linear regression forecast to your seasonally adjusted forecast, recommend to your General Manager which forecast for periods 18, 19, 20 and 21 she should use and why.
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