Results: fegsub.sas

The SGScatter Procedure

The SGScatter Procedure

The SGScatter Procedure

Regression of city mileage on engine displacement (engine size <= 2.5 litre)

mileage in mpg, displacement in 100cc (e.g. 10 is 1000cc = 1 litre)

The REG Procedure

Model: MODEL1

Dependent Variable: city

The Reg Procedure

MODEL1

Fit

city

Number of Observations

Number of Observations Read 35
Number of Observations Used 35

Analysis of Variance

Analysis of Variance
Source DF Sum of
Squares		 Mean
Square		 F Value Pr > F
Model 1 662.71727 662.71727 161.45 <.0001
Error 33 135.45415 4.10467    
Corrected Total 34 798.17143      

Fit Statistics

Root MSE 2.02600 R-Square 0.8303
Dependent Mean 25.77143 Adj R-Sq 0.8252
Coeff Var 7.86141    

Parameter Estimates

Parameter Estimates
Variable DF Parameter
Estimate		 Standard
Error		 t Value Pr > |t|
Intercept 1 49.15903 1.87219 26.26 <.0001
displ 1 -1.20201 0.09460 -12.71 <.0001

Regression of city mileage on engine displacement (engine size <= 2.5 litre)

mileage in mpg, displacement in 100cc (e.g. 10 is 1000cc = 1 litre)

The REG Procedure

Model: MODEL1

Dependent Variable: city

Observation-wise Statistics

city

Diagnostic Plots

Fit Diagnostics

Panel of fit diagnostics for city.

Residual Plots

displ

Scatter plot of residuals by displ for city.

Fit Plot

Scatterplot of city by displ overlaid with the fit line, a 95% confidence band and lower and upper 95% prediction limits.

Regression of city mileage on engine displacement (engine size <= 2.5 litre)

mileage in mpg, displacement in 100cc (e.g. 10 is 1000cc = 1 litre)

The Print Procedure

Data Set WORK.NEW

Obs displ city yhat resid
1 10 39 37.1390 1.86103
2 13 36 33.5330 2.46705
3 13 36 33.5330 2.46705
4 15 33 31.1289 1.87106
5 16 30 29.9269 0.07307
6 16 32 29.9269 2.07307
7 16 26 29.9269 -3.92693
8 16 30 29.9269 0.07307
9 18 25 27.5229 -2.52292
10 18 25 27.5229 -2.52292
11 18 28 27.5229 0.47708
12 18 28 27.5229 0.47708
13 18 28 27.5229 0.47708
14 18 23 27.5229 -4.52292
15 18 25 27.5229 -2.52292
16 19 27 26.3209 0.67908
17 19 28 26.3209 1.67908
18 20 25 25.1189 -0.11891
19 20 23 25.1189 -2.11891
20 20 22 25.1189 -3.11891
21 20 24 25.1189 -1.11891
22 20 24 25.1189 -1.11891
23 22 24 22.7149 1.28510
24 22 22 22.7149 -0.71490
25 22 24 22.7149 1.28510
26 22 23 22.7149 0.28510
27 22 23 22.7149 0.28510
28 23 20 21.5129 -1.51289
29 23 20 21.5129 -1.51289
30 24 23 20.3109 2.68911
31 24 23 20.3109 2.68911
32 24 23 20.3109 2.68911
33 24 19 20.3109 -1.31089
34 25 20 19.1089 0.89112
35 25 21 19.1089 1.89112