In: Statistics and Probability
1- Nelson Industries manufactures a part for a type of aircraft engine that is becoming obsolete. The sales history for the last 10 years is as follows:
year sales
Dec-98 945
Dec-99 875
Dec-00 760
Dec-01 690
Dec-02 545
Dec-03 420
Dec-04 305
Dec-05 285
Dec-06 250
Dec-07 210
1- Nelson Industries manufactures a part for a type of aircraft engine that is becoming obsolete. The sales history for the last 10 years is as follows:
year sales
Dec-98 945
Dec-99 875
Dec-00 760
Dec-01 690
Dec-02 545
Dec-03 420
Dec-04 305
Dec-05 285
Dec-06 250
Dec-07 210
Estimate the regression model for a linear time trend of sales.
Yt = 1016.7 - 88.76×t
What is the root-mean-squared error of the linear regression estimates for these 10 years?
MSD |
2357.52 |
root-mean-squared error = sqrt(2357.52)
=48.5543
Using this model, estimate sales for year 11.
When t=11,
Estimated sales =1016.7 - 88.76*11
=40.34
Trend Analysis for sales
Method
Model type |
Linear Trend Model |
Data |
sales |
Length |
10 |
NMissing |
0 |
Fitted Trend Equation
Yt = 1016.7 - 88.76×t |
Accuracy Measures
MAPE |
12.03 |
MAD |
40.79 |
MSD |
2357.52 |
Forecasts
Period |
Forecast |
11 |
40.3333 |
Model Summary
Time |
sales |
Trend |
Detrend |
1 |
945 |
927.909 |
17.0909 |
2 |
875 |
839.152 |
35.8485 |
3 |
760 |
750.394 |
9.6061 |
4 |
690 |
661.636 |
28.3636 |
5 |
545 |
572.879 |
-27.8788 |
6 |
420 |
484.121 |
-64.1212 |
7 |
305 |
395.364 |
-90.3636 |
8 |
285 |
306.606 |
-21.6061 |
9 |
250 |
217.848 |
32.1515 |
10 |
210 |
129.091 |
80.9091 |