Two Level Factorial Design: Difference between revisions

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{{Reference Example|{{Banner DOE Reference Examples}}}}
{{Reference Example|{{Banner DOE Reference Examples}}}}
This example validates the calculation of the two level factorial design in DOE++.
This example validates the calculation of the two level factorial design in Weibull++.


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{{Reference_Example_Heading1}}

Latest revision as of 21:08, 18 September 2023

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Two Level Factorial Design

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.

Two level responses.png


Two level anova.png
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