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DOE++ Features Summary
Utilities for Refining and
Extending the Analysis
Variability Analysis
For designs with more than
one replicate,
DOE++
gives you the ability to determine the variability of the
response(s) across runs and to analyze that standard deviation
information. This offers valuable insight into the sources of
variation within the experimental data.
 
Diagnostics for a Closer Look
The Diagnostics window provides run-by-run
results including fitted values, residuals, leverage and Cook’s
distance measure to help you assess the model at each data point
for potential outliers and influential observations.
Response Prediction for Untested Treatments
DOE++ 's
Prediction window allows you to enter your own combinations of
factor settings and returns response values, complete with
confidence metrics, based on the fitted model.
Optimization for Your Desired Outcome
DOE++
can help you determine the best factor settings to achieve your
goals for the response(s) in your analysis. For each response,
you can:
Specify whether you
want to minimize the response, maximize it or bring it
as close as possible to a particular target value.
Designate maximum,
minimum and/or target values per the analysis objective.
Specify how much
emphasis is placed on these values when determining the
desirability of solutions (i.e. how narrowly to
define "desirable").
Specify how
important the optimization of each response is with
respect to the optimization of other responses included
in the analysis (i.e. which response is most
important to optimize).
In addition, you can set
boundaries or constraints on each factor to be used in the
optimization process.
DOE++ will search
for the most effective combinations of factor settings and will
rank the solutions according to their desirability.
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