minitab 全因子doe如何得出coef
3因子2个因子2水平,一个因子3水平
StdOrder RunOrder PtType Blocks A B C
1 1 1 1 1 1 1 18
2 2 1 1 1 1 2 20
3 3 1 1 1 2 1 20
4 4 1 1 1 2 2 24
5 5 1 1 2 1 1 12
6 6 1 1 2 1 2 14
7 7 1 1 2 2 1 16
8 8 1 1 2 2 2 18
9 9 1 1 3 1 1 5
10 10 1 1 3 1 2 8
11 11 1 1 3 2 1 10
12 12 1 1 3 2 2 13
General Linear Model: C8 versus A, B, C
Factor Type Levels Values
A fixed 3 1, 2, 3
B fixed 2 1, 2
C fixed 2 1, 2
Analysis of Variance for C8, using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F P
A 2 264.667 264.667 132.333 397.00 0.003
B 1 48.000 48.000 48.000 144.00 0.007
C 1 21.333 21.333 21.333 64.00 0.015
A*B 2 2.000 2.000 1.000 3.00 0.250
A*C 2 0.667 0.667 0.333 1.00 0.500
B*C 1 0.333 0.333 0.333 1.00 0.423
Error 2 0.667 0.667 0.333
Total 11 337.667
S = 0.577350 R-Sq = 99.80% R-Sq(adj) = 98.91%
StdOrder RunOrder PtType Blocks A B C
1 1 1 1 1 1 1 18
2 2 1 1 1 1 2 20
3 3 1 1 1 2 1 20
4 4 1 1 1 2 2 24
5 5 1 1 2 1 1 12
6 6 1 1 2 1 2 14
7 7 1 1 2 2 1 16
8 8 1 1 2 2 2 18
9 9 1 1 3 1 1 5
10 10 1 1 3 1 2 8
11 11 1 1 3 2 1 10
12 12 1 1 3 2 2 13
General Linear Model: C8 versus A, B, C
Factor Type Levels Values
A fixed 3 1, 2, 3
B fixed 2 1, 2
C fixed 2 1, 2
Analysis of Variance for C8, using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F P
A 2 264.667 264.667 132.333 397.00 0.003
B 1 48.000 48.000 48.000 144.00 0.007
C 1 21.333 21.333 21.333 64.00 0.015
A*B 2 2.000 2.000 1.000 3.00 0.250
A*C 2 0.667 0.667 0.333 1.00 0.500
B*C 1 0.333 0.333 0.333 1.00 0.423
Error 2 0.667 0.667 0.333
Total 11 337.667
S = 0.577350 R-Sq = 99.80% R-Sq(adj) = 98.91%
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