Shown here are the data for y and three predictors, x1, x2, and x3. A multiple regression analysis has been done on these data; the Minitab results are given. Comment on the outcome of the analysis in light of the data.
|
y
|
x1
|
x2
|
x3
|
|
94
|
21
|
1
|
204
|
|
97
|
25
|
0
|
198
|
|
93
|
22
|
1
|
184
|
|
95
|
27
|
0
|
200
|
|
90
|
29
|
1
|
182
|
|
91
|
20
|
1
|
159
|
|
91
|
18
|
1
|
147
|
|
94
|
25
|
0
|
196
|
|
98
|
26
|
0
|
228
|
|
99
|
24
|
0
|
242
|
|
90
|
28
|
1
|
162
|
|
92
|
23
|
1
|
180
|
|
96
|
25
|
0
|
219
|
Regression Analysis: Y versus X1,X2,X3
The regression equation is Y = 87.9 - 0.256 X1 - 2.71 X2 + 0.0706 X3
|
Predictor
|
Coef
|
SE Coef
|
T
|
P
|
|
Constant
|
87.890
|
3.445
|
25.51
|
0.000
|
|
X1
|
-0.25612
|
0.08317
|
-3.08
|
0.013
|
|
X2
|
-2.7137
|
0.7306
|
-3.71
|
0.005
|
|
X3
|
0.07061
|
0.01353
|
5.22
|
0.001
|
|
S = 0.850311
|
R-Sq = 94.1%
|
R-Sq(adj) = 92.1%
|