View source for Two Level Factorial Design

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This example validates the calculation of the two level factorial design in Weibull++.

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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.   

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{| {{Table}}
!colspan="2" | Factor
!rowspan="2" style="vertical-align:top"|Treatment Combination
!colspan="3" | Replicate
|-
!style="background:#f0f0f0;"|A
!style="background:#f0f0f0;"|B
!style="background:#f0f0f0;"|1
!style="background:#f0f0f0;"|2
!style="background:#f0f0f0;"|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

|}
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Table 6-1 from the book shows the ANOVA table for this experiment.

{| {{Table}}
!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||||||
|-
|}

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The results from the software are the same as the results from the book. Both show that A and B are significant factors.

[[Image:two_level_responses.png|center]]


[[Image:two_level_anova.png|center]]