Regression Data
t Season DPI RS MR
1 Q1 2743 274 13,7
2 Q2 2692 262 14,4
3 Q3 2723 266 12,6
4 Q4 2777 269 14,2
5 Q1 2784 273 15,1
6 Q2 2777 269 16,2
7 Q3 2814 271 17,4
8 Q4 2809 265 17,7
9 Q1 2795 264 17,4
10 Q2 2825 265 16,7
11 Q3 2829 266 16,2
12 Q4 2833 273 14
13 Q1 2843 275 13,1
14 Q2 2867 284 12,8
15 Q3 2903 288 13,6
16 Q4 2960 296 13,5
17 Q1 3033 302 13,3
18 Q2 3066 307 14
19 Q3 3103 305 14,5
20 Q4 3119 311 13,7
21 Q1 3124 315 13,1
22 Q2 3190 320 12,8
23 Q3 3157 326 12,1
24 Q4 3179 324 11,7
25 Q1 3228 329 10,6
26 Q2 3281 336 10,3
27 Q3 3273 346 10,2
28 Q4 3266 348 9,7
29 Q1 3295 341 9,1
30 Q2 3242 348 10,3
31 Q3 3286 353 10,5
32 Q4 3336 350 10,8
33 Q1 3280 357 10,1
34 Q2 3386 359 10,4
35 Q3 3407 359 10,5
36 Q4 3443 367 10,4
37 Q1 3474 365 10,8
38 Q2 3451 367 10,7
39 Q3 3467 372 10
40 Q4 3493 369 9,8
Index
RS
40 36 32 28 24 20 16 12 8 4 375
350
325
300
275
250
Time Series Plot of RS
RS zaman sersisini zamana (t) göre bir doğrusal trendi olduğu izlenimi ediniyoruz. Bu saptamayı yaptıktan sonra
1. Bir basit Doğrusal Regresyon modeli önerip gerekli analizleri yapalım.
Regression Analysis: RS versus t
The regression equation is RS = 248 + 3,21 t
Predictor Coef SE Coef T P Constant 247,550 2,639 93,82 0,000 t 3,2122 0,1122 28,64 0,000
S = 8,18794 R-Sq = 95,6% R-Sq(adj) = 95,5%
Analysis of Variance
Source DF SS MS F P Regression 1 54996 54996 820,32 0,000 Residual Error 38 2548 67
Total 39 57544
Unusual Observations
Obs t RS Fit SE Fit Residual St Resid 1 1,0 274,00 250,76 2,54 23,24 2,99R 11 11,0 266,00 282,88 1,68 -16,88 -2,11R
R denotes an observation with a large standardized residual.
Durbin-Watson statistic = 0,353702 Predicted Values for New Observations
New
Obs Fit SE Fit 95% CI 95% PI 1 379,25 2,64 (373,91; 384,59) (361,83; 396,67) Values of Predictors for New Observations
New Obs t 1 41,0
Re s idua l
Percent
2 0 1 0 0 -1 0 -2 0 9 9 9 0
5 0
1 0 1
Fitte d V a lue
Residual
3 5 0 3 0 0
2 5 0 2 0 1 0 0 -1 0 -2 0
Re s idua l
Frequency
2 0 1 0 0 -1 0 1 6
1 2 8
4 0
O bs e rv a tion O rde r
Residual
4 0 3 5 3 0 2 5 2 0 1 5 1 0 5 1 2 0 1 0 0 -1 0 -2 0
Norm a l P roba bility Plot of the Re s idua ls Re s idua ls Ve rs us the Fitte d V a lue s
His togra m of the Re s idua ls Re s iduals Ve rs us the Orde r of the Da ta R e sidual Plots for R S
