In: Statistics and Probability
Consider the monthly time series shown in the table.
Month |
t |
Y |
January |
1 |
185 |
February |
2 |
192 |
March |
3 |
189 |
April |
4 |
201 |
May |
5 |
195 |
June |
6 |
199 |
July |
7 |
206 |
August |
8 |
203 |
September |
9 |
208 |
October |
10 |
209 |
November |
11 |
218 |
December |
12 |
216 |
Minitab > Stat > Regression > Regression > Fit regression model
a)
E(Yt) = β0 + β1t
E(Yt) = 184 + 2.731*t
b)
Again Minitab > Stat > Regression > Regression > Prediction
If t = 13, E(Y13) = 219.5
If t = 14, E(Y14) = 222.231
c)
Prediction intervals
If t = 13
95% PI = (211.067, 227.933)
If t = 14
95% PI = (213.504, 230.958)