Applythe \"forward\" method to choose the best model of regression, compute anov
ID: 3202313 • Letter: A
Question
Applythe "forward" method to choose the best model of regression, compute anova tabble.
Is this model is significance
number of observation
time of deliver
number of cases
Distannce
number of machines
number of establichements of the machines
1
9.95
2
50
1
1
2
24.45
8
110
1
1
3
31.75
11
120
2
1
4
35
10
550
2
2
5
25.02
8
295
1
1
6
16.86
4
200
1
1
7
14.38
2
375
1
1
8
9.6
2
52
1
1
9
24.35
9
100
1
1
10
27.5
8
300
2
1
11
17.08
4
412
2
2
12
37
11
400
3
2
13
41.95
12
500
3
3
14
11.66
2
360
1
1
15
21.65
4
205
2
2
16
17.89
4
400
2
1
17
69
20
600
4
4
18
10.3
1
585
1
1
19
34.93
10
540
2
1
20
46.59
15
250
3
2
21
44.88
15
290
3
1
22
54.12
16
510
3
3
23
56.63
17
590
2
2
24
22.13
6
100
2
1
25
21.15
5
400
1
1
Continuación Problema 1
number of variables in models
P
Variables in model
SSE
1
2
X2
4622.704
1
2
X4
2686.158
1
2
X3
1842.104
1
2
X1
220.0926
2
3
X2, x4
2615.901
2
3
X2, x3
1699.745
2
3
X3, x4
1695.457
2
3
X1, x3
169.7308
2
3
X1, x2
115.1735
2
3
X1, x4
103.6201
3
4
X2, x3, x4
1630.844
3
4
X1, x3, x4
102.0978
3
4
X1, x2, x3
90.2503
3
4
X1, x2, x4
63.4107
4
5
X1, x2, x3, x4
61.597
number of observation
time of deliver
number of cases
Distannce
number of machines
number of establichements of the machines
1
9.95
2
50
1
1
2
24.45
8
110
1
1
3
31.75
11
120
2
1
4
35
10
550
2
2
5
25.02
8
295
1
1
6
16.86
4
200
1
1
7
14.38
2
375
1
1
8
9.6
2
52
1
1
9
24.35
9
100
1
1
10
27.5
8
300
2
1
11
17.08
4
412
2
2
12
37
11
400
3
2
13
41.95
12
500
3
3
14
11.66
2
360
1
1
15
21.65
4
205
2
2
16
17.89
4
400
2
1
17
69
20
600
4
4
18
10.3
1
585
1
1
19
34.93
10
540
2
1
20
46.59
15
250
3
2
21
44.88
15
290
3
1
22
54.12
16
510
3
3
23
56.63
17
590
2
2
24
22.13
6
100
2
1
25
21.15
5
400
1
1
Explanation / Answer
the best model for regression is last , which includes all the four variable x1,x2, x3, and x4 and corresponding information is given as
Analysis of Variance Source DF Sum of Mean F Value Pr > F Squares Square Model 4 6044.34771 1511.09 490.64 <.0001 Error 20 61.597 3.07985 Corrected Total 24 6105.9447 Variable Parameter Standard Type II SS F Value Pr > F Estimate Error Intercept 1.06813 0.92773 4.08258 1.33 0.2632 x1 2.48423 0.11007 1568.75 509.36 <.0001 x2 0.00855 0.00236 40.5008 13.15 0.0017 x3 0.62237 0.81102 1.81369 0.59 0.4518 x4 2.29392 0.74855 28.9232 9.39 0.0061Related Questions
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