Regression
Statistics
Multiple R 0.7423494
R Square 0.5510826
Adjusted R 0.4228205
Square
Standard 0.1756333
Error
Observations 10
ANOVA
df SS MS
Regression 2 0.26507072 0.132535
Residual 7 0.21592928 0.030847
Total 9 0.481
ANOVA Cont.
F Significance
F
Regression 4.2965341 0.060615349
Residual
Total
Coefficient Standard t Stat
s Error
Intercept -2.969425 3.436814041 -0.864005
x1 -0.00447 0.001549131 -2.88535
x2 0.2187938 0.083909076 2.607511
P-value Lower 95% Upper 95%
Intercept 0.4162061 -11.09619346 5.157343
x1 0.0234716 -0.008132894 -0.000807
x2 0.03504 0.020380542 0.417207
Lower Upper 95.0%
95.0%
Intercept -11.09619 5.157342571
x1 -0.008133 -0.000806674
x2 0.0203805 0.417207129
RESIDUAL
OUTPUT
Observation Predicted Residuals Standard
y Residuals
1 5.2404297 -0.040429737 -0.230194
2 5.3733586 -0.073358605 -0.417681
3 5.6410945 -0.241094485 -1.372715
4 5.4752429 0.124757057 0.710327
5 5.3969089 0.103091065 0.586968
6 5.4105622 0.289437755 1.647967
7 5.4206848 0.079315157 0.451595
8 5.3981103 0.001889654 0.010759
9 5.3710661 -0.171066064 -0.973996
10 4.9725418 -0.072541798 -0.41303
Durbin Watson
Stat
1.333901624
This data was
sued to make
the first
Check for
Auto - Graph
Observation Observed y Lagged Residuals
Residuals
2 5.3 -0.040429737 -0.073359
3 5.4 -0.073358605 -0.241094
4 5.6 -0.241094485 0.124757
5 5.5 0.124757057 0.103091
6 5.7 0.103091065 0.289438
7 5.5 0.289437755 0.079315
8 5.4 0.079315157 0.00189
9 5.2 0.001889654 -0.171066
10 4.9 -0.171066064 -0.072542
This data was
used for the
second Check
for Auto
Observation Residuals
1 -0.04043
2 -0.073359
3 -0.241094
4 0.1247571
5 0.1030911
6 0.2894378
7 0.0793152
8 0.0018897
9 -0.171066
10 -0.072542
Observation Observed y Squared
Residuals
1 5.2 #REF!
2 5.3 0.005381485
3 5.4 0.058126551
4 5.6 0.015564323
5 5.5 0.010627768
6 5.7 0.083774214
7 5.5 0.006290894
8 5.4 3.57079E-06
9 5.2 0.029263598
10 4.9 0.005262313