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Material Type: Assignment; Class: Applied Regression Analysis; Subject: STATISTICS; University: University of Wisconsin - Madison; Term: Spring 2004;
Typology: Assignments
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Stat 333 Spring 2004 1/30/
The variance and standard deviation for b 1 are given by the following:
V (b 1 ) =
σ^2
SXX
sd(b 1 ) =
σ √ SXX
est.sd(b 1 ) =
s √ SXX
Note that b 1 is the estimator of β 1 such that b 1 =
. When constructing the confidence interval
for β 1 , we should know the following facts:
(1) β 1 is the parameter of interest and it is fixed, not random.
(2) b 1 is a random variable and it has the normal distribution with mean β 1 and variance
σ
2
(3) From (2), we know that
b 1 − β 1
σ/
has the standard normal distribution, N (0, 1). Since σ^2
is unknown, we use s^2 to estimate σ^2 , where s^2 = MSE = SSE/(n − 2). Therefore,
b 1 − β 1
s/
has the t-distribution with (n-2) degrees of freedom, i.e.,
b 1 − β 1
s/
∼ tn− 2
With these facts, we have
(
−t(n − 2 , 1 −
α
2
b 1 − β 1
s/
< t(n − 2 , 1 −
α
2
)
= 1 − α
That is,
(
b 1 − t(n − 2 , 1 −
α
2
s √ SXX
< β 1 < b 1 + t(n − 2 , 1 −
α
2
s √ SXX
)
= 1 − α
So the 100(1 − α)% confidence interval for β 1 is
b 1 ± t(n − 2 , 1 −
α
2
s √ SXX
4268 CSSC [email protected] Ting-Li Lin