Experimental design techniques are designed to discover what factors or interactions have a significant impact on a response variable. Our SPC for Excel provides an easy-to-use design of experiments (DOE) methodology in the Excel environment you know.
The software contains two-level full factorial designs (up to 7 factors), fractional factorial designs (29 different designs, up to 15 factors), and Plackett-Burman designs (up to 27 factors).
The output includes the ANOVA table for the factors and interactions, the model in both coded and uncoded format, normal and half-normal plot of effects and much more. A complete list of features is given below.
Watch a Video Highlighting SPC for Excel's Experimental Design Capabilities!
Experimental Design Features
Design table analysis
ANOVA Table for factors and interactions
ANOVA for model
Model for coded and actual factors
Coefficient of variation
Adjusted R square
R square prediction
Normal plot of effects
Half-normal plot of effects
Two factor charts
Internally studentized residuals
Externally studentized residuals
Potential outliers in red
Residuals charts (raw, standardized, internally or externally studentized residuals)
Versus predicted values
Versus actual run number
Predicted vs actual
DFFITS, Cook's distance and leverage versus actual run number
DOE optimization chart
Easily select effects to include/exclude in the analysis
p values < 0.05 in red