In: Statistics and Probability
year |
quarter |
period |
EMPLOYED INDIVIDUALS (2016-2019) |
|
1 |
1 |
1 |
4169189.0 |
|
1 |
2 |
2 |
4262978.0 |
|
1 |
3 |
3 |
4306669.0 |
|
1 |
4 |
4 |
4310845.0 |
|
2 |
1 |
5 |
4338992.0 |
|
2 |
2 |
6 |
4387124.0 |
|
2 |
3 |
7 |
4372602.0 |
|
2 |
4 |
8 |
4431912.0 |
|
3 |
1 |
9 |
4495638.0 |
|
3 |
2 |
10 |
4520797.0 |
|
3 |
3 |
11 |
4558422.0 |
|
3 |
4 |
12 |
4582166.0 |
|
4 |
1 |
13 |
4648638.0 |
|
4 |
2 |
14 |
4657061.0 |
|
4 |
3 |
15 |
4631183.0 |
|
4 |
4 |
16 |
4715879.0 |
|
Number of people |
With these time series:
Use regression analysis to present an equation that describes your time series. Using this equation forecast two periods ahead. (If your time series presents seasonality, remember to construct dummy variables to include seasonality in your equation).
Data | Forecasts and Error Analysis | |||||||
Period | Demand (y) | Period(x) | Forecast | Error | Absolute | Squared | Abs Pct Err | |
Period 1 | 4169189 | 1 | 4208773 | -39583.7 | 39583.67 | 1.57E+09 | 00.95% | |
Period 2 | 4262978 | 2 | 4242520 | 20457.56 | 20457.56 | 4.19E+08 | 00.48% | |
Period 3 | 4306669 | 3 | 4276268 | 30400.79 | 30400.79 | 9.24E+08 | 00.71% | |
Period 4 | 4310845 | 4 | 4310016 | 829.0235 | 829.0235 | 687280 | 00.02% | |
Period 5 | 4338992 | 5 | 4343764 | -4771.75 | 4771.746 | 22769556 | 00.11% | |
Period 6 | 4387124 | 6 | 4377512 | 9612.485 | 9612.485 | 92399874 | 00.22% | |
Period 7 | 4372602 | 7 | 4411259 | -38657.3 | 38657.28 | 1.49E+09 | 00.88% | |
Period 8 | 4431912 | 8 | 4445007 | -13095.1 | 13095.05 | 1.71E+08 | 00.30% | |
Period 9 | 4495638 | 9 | 4478755 | 16883.18 | 16883.18 | 2.85E+08 | 00.38% | |
Period 10 | 4520797 | 10 | 4512503 | 8294.409 | 8294.409 | 68797218 | 00.18% | |
Period 11 | 4558422 | 11 | 4546250 | 12171.64 | 12171.64 | 1.48E+08 | 00.27% | |
Period 12 | 4582166 | 12 | 4579998 | 2167.871 | 2167.871 | 4699663 | 00.05% | |
Period 13 | 4648638 | 13 | 4613746 | 34892.1 | 34892.1 | 1.22E+09 | 00.75% | |
Period 14 | 4657061 | 14 | 4647494 | 9567.332 | 9567.332 | 91533848 | 00.21% | |
Period 15 | 4631183 | 15 | 4681241 | -50058.4 | 50058.44 | 2.51E+09 | 01.08% | |
Period 16 | 4715879 | 16 | 4714989 | 889.7941 | 889.7941 | 791733.6 | 00.02% | |
Total | 9.31E-10 | 292332.4 | 9.01E+09 | 06.59% | ||||
Intercept | 4175024.9 | Average | 5.82E-11 | 18270.77 | 5.63E+08 | 00.41% | ||
Slope | 33747.7691 | Bias | MAD | MSE | MAPE | |||
SE | 25373.82 | |||||||
Forecast | 4748736.98 | 17 | ||||||
Forecast | 4748736.98 | 18 | Correlation | 0.988561 | ||||
Coefficient of determination | 0.977252 |