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Two Level Factorial Design
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This example validates the calculation of the two level factorial design in Weibull++.
Reference Case
The data are from an example on page 223 in the book Design and Analysis of Experiments by Douglas C. Montgomery, John Wiley & Sons, 2001.
Data
| Factor
|
Treatment Combination
|
Replicate
|
| A
|
B
|
1
|
2
|
3
|
| - |
- |
A low, B low |
28 |
25 |
27
|
| + |
- |
A high, B low |
36 |
32 |
32
|
| - |
+ |
A low, B high |
18 |
19 |
23
|
| + |
+ |
A high, B high |
31 |
30 |
29
|
Result
Table 6-1 from the book shows the ANOVA table for this experiment.
| Source of Variation
|
Sum of Squares
|
Degrees of Freedom
|
Mean Square
|
F value
|
P-Value
|
| A |
208.33 |
1 |
208.33 |
53.15 |
0.0001
|
| B |
75.00 |
1 |
75.00 |
19.13 |
0.0024
|
| AB |
8.33 |
1 |
8.33 |
2.13 |
0.1826
|
| Error |
31.34 |
8 |
3.92 |
|
|
| Total |
323.00 |
11 |
|
|
|
Results in DOE++
The results from the software are the same as the results from the book. Both show that A and B are significant factors.
