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
Full factorials
Fractional factorials
Plackett- Burman
Design table analysis
ANOVA Table for factors and interactions
ANOVA for model
Model for coded and actual factors
Design statistics
Average
Standard deviation
Coefficient of variation
R square
Adjusted R square
PRESS
R square prediction
Normal plot of effects
Half-normal plot of effects
Effects charts
Two factor charts
Residuals analysis
Residuals
Leverage
Standardized residuals
Internally studentized residuals
Externally studentized residuals
DFFITS
Cook's distance
Potential outliers in red
Residuals charts (raw, standardized, internally or externally studentized residuals)
Normal plot
Versus predicted values
Versus actual run number
Other charts
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