Design and analysis of experiment (DOE)
This module designs a two-level multifactorial orthogonal plan 2^(n–k) and perform its analysis. The DOE module has two parts, Design for the experimental design before carying out experiments which will find optimal combinations of factor levels to gain maximum information at a reasonable number of experiments and part Analysis which will analyse results of the planned experiment. The main goal of DOE is to find which of the factors included in the model have considerable influence on one outcome of the experiment. The outcome is called response and it can typically be yield, energy consumption, costs, rate of non-conforming product units, blood pressure etc.

PDF Design and analysis of experiment (DOE) - Pdf manual

Output: 
 Text/numerical output: Graphical output: 

Design type
Design definition
Design charcteristics
Number of factors and replication
No of experiments needed
Alias structure analysis
Main effects and interactions
Computed effects and regression coefficients
Effects standard deviations
Analysis of variance (ANOVA)
Total variability
Explained variability
Residual variability
Influence of factors to variance
Detailed analysis - Taguchi approach
Means(-/+), Variances(-/+)
Influence ratios(+/-)
Residual analysis
Response prediction

Plot of absolute effects 
Sorted effects
Squared effects
Diagnostic Effects QQ-plot
Deviations in QQplot
Effects plot
Interaction plot

Design of Experiments input dialog box
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Analysis of Designed experiments input dialog box
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Example output from DOE Analysis. 2^(6-1) design, 6 efects, 16x2 experiments
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Graphical outputs of the module is essential and highly informative part of the analysis, revealing most influential factors and interactions for the first sight. Some of the plots are shown below.

Effects and interaction, assessment of influence
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Detailed visualization of all pairs if second order interactions
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Overall interaction plot
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