Andres AradillasLopez
1. Exercise 10.6
(a) The variables x and y are reversed: Slope gives the change in y for a change in x.
(b) The population regression line has intercept
β
0
and slope
β
1
(not
b
0
and
b
1
). (c)
The estimate ˆ
μ
y
=
b
0
+
b
1
x
*
is more accurate when
x
*
is closed to ¯
x
, so the width
of the conFdence interval grows with (
x
*
−
¯
x
)
2
.
2. Exercise 10.8
The table below gives two sets of answers: those found with critical values from table
D, and those found with software. In each case, the margin of error is
t
*
SE
b
1
=
6
.
31
t
*
, with
df
=
n
−
2.
df
b
1
t
*
Interval
t
*
Interval
(a)
23
12.1
2.069
0.9554 to 25.1554
2.0687
0.9532 to 25.1532
(b)
23
6.1
2.069
6.9554 to 19.1554
2.0687
6.9532 to 19.1532
(c)
98
12.1
1.990*
0.4569 to 24.6569
1.9845
0.4220 to 24.6220
*Note that for (c), if we use Table D, we take
df
= 80.
3. Exercise 10.10
(a) The plot (below) shows a strong linear relationship with no striking outliers.
(b) The regression line (shown on the plot) is ˆ
y
= 1059 + 1
.
3930
x
. (c) In the plot
(below), it appears that for large x values, many residuals are negative. (d) A
stemplot or histogram suggests a slight left skew. (e) To test for a relationship, we
test
H
0
:
β
1
= 0 vs.
H
a
:
β
1
n
= 0 (or equivalently, use
ρ
in place of
β
1
). (f) The test
statistic and Pvalue are given in the Minitab output below:
t
.
= 15
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 Spring '08
 Rush
 Statistics, Regression Analysis, Errors and residuals in statistics, Minitab output

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