In: Statistics and Probability
FORECASTING
A major source of revenue in Jacksonville is a county sales tax on certain types of goods and services. For the most recent 4 years (2015 to 2018), quarterly sales tax revenue (in millions of dollars) has been collected. These values are shown in the following table:
Year |
Quarter |
Sales Tax Revenue ($1,000,000) |
2015 |
1 |
218 |
2015 |
2 |
247 |
2015 |
3 |
243 |
2015 |
4 |
292 |
2016 |
1 |
225 |
2016 |
2 |
254 |
2016 |
3 |
255 |
2016 |
4 |
299 |
2017 |
1 |
234 |
2017 |
2 |
265 |
2017 |
3 |
264 |
2017 |
4 |
327 |
2018 |
1 |
250 |
2018 |
2 |
283 |
2018 |
3 |
389 |
2018 |
4 |
356 |
Use multiple regression to estimate the trend and seasonal components of this time series. Explain the meaning of each estimated coefficient that results from the regression procedure. Then, provide a forecast for each quarter of 2019.
data
y | t | Q1 | Q2 | Q3 |
218 | 1 | 1 | 0 | 0 |
247 | 2 | 0 | 1 | 0 |
243 | 3 | 0 | 0 | 1 |
292 | 4 | 0 | 0 | 0 |
225 | 5 | 1 | 0 | 0 |
254 | 6 | 0 | 1 | 0 |
255 | 7 | 0 | 0 | 1 |
299 | 8 | 0 | 0 | 0 |
234 | 9 | 1 | 0 | 0 |
265 | 10 | 0 | 1 | 0 |
264 | 11 | 0 | 0 | 1 |
327 | 12 | 0 | 0 | 0 |
250 | 13 | 1 | 0 | 0 |
383 | 14 | 0 | 1 | 0 |
389 | 15 | 0 | 0 | 1 |
356 | 16 | 0 | 0 | 0 |
Excel regression output
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.86072103 | |||||
R Square | 0.740840692 | |||||
Adjusted R Square | 0.646600944 | |||||
Standard Error | 32.58867274 | |||||
Observations | 16 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 4 | 33395.2 | 8348.8 | 7.861233775 | 0.0030201 | |
Residual | 11 | 11682.2375 | 1062.021591 | |||
Total | 15 | 45077.4375 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 244.0625 | 24.44150455 | 9.985575948 | 7.50039E-07 | 190.2671112 | 297.8578888 |
t | 7.44375 | 1.821762189 | 4.086016302 | 0.001801683 | 3.434078458 | 11.45342154 |
Q1 | -64.41875 | 23.68290845 | -2.720052317 | 0.01992959 | -116.54448 | -12.29302 |
Q2 | -16.3625 | 23.32993925 | -0.701352019 | 0.497652968 | -67.71135007 | 34.98635007 |
Q3 | -23.30625 | 23.11557079 | -1.008248951 | 0.334999183 | -74.18327827 | 27.57077827 |
y^= 244.0625 + 7.44375 t -64.41875 Q1 -16.3625 Q2 -23.30625 Q3
t | predicted |
17 | 306.1875 |
18 | 361.6875 |
19 | 362.1875 |
20 | 392.9375 |