Results for: Sheet1
Regression Analysis: Y versus X1, X2, X3
The regression equation is
Y = 158  1.14 X1  0.442 X2  13.5 X3
Predictor
Coef
SE Coef
T
P
Constant
158.49
18.13
8.74
0.000
X1
1.1416
0.2148
5.31
0.000
X2
0.4420
0.4920
0.90
0.374
X3
13.470
7.100
1.90
0.065
S = 10.0580
RSq = 68.2%
RSq(adj) = 65.9%
Analysis of Variance
Source
DF
SS
MS
F
P
Regression
3
9120.5
3040.2
30.05
0.000
Residual Error
42
4248.8
101.2
Total
45
13369.3
Source
DF
Seq SS
X1
1
8275.4
X2
1
480.9
X3
1
364.2
We notice that the coefficients have signs which we could expect. For example, x8 has
a negative sign. It should have a negative impact on the number of games won if the
opponent is able to attain more running yards. Can you interpret each coefficient in
context here?
We see that the ANOVA has an F statistics of 29.44 with a pvalue of 0. This means
our model is significant.
Note that the Adjusted Rsquared value is 76%. That is a
relatively good fit. We see that s = 1.70624 and the value of MSE is 2.911.
Note also that each coefficient is significant on its own. X2, x7 and x8 all have
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 Summer '10
 Bell
 Statistics, Normal Distribution, Regression Analysis, Errors and residuals in statistics, Prediction interval, X1 X2 X3

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