¥Test for
Significance of Linear Regression
HThis is
done by testing whether additional parameters significantly improve the
fit
åFor
simple case![](space.gif)
H![](space.gif)
Y
=
b0 +
b1X1 +
e ![](space.gif)
H![](space.gif)
H
0:
b1 =
0
å![](space.gif)
H
1:
b1 0
åFor
general case ![](space.gif)
å![](space.gif)
Y =
b0 +
b1X1 +
b2X2 +
É +
bq-1Xq-1 +
bqXq +
É +
bp-1Xp-1 +
e
å![](space.gif)
H
0:
bq =
bq+1 =
...
=
bp-1 =
0
å![](space.gif)
H
a:
bk 0, for some k, q ² k ² p-1
å
åFreg is the F-statistic
for determining if the Full model significantly improved on the
reduced model
íNOTE: This F-statistic is
assumed to have a central F-distribution. This is not the case when there is a lack of fit