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Additional assumption features
Fitting distributions to data
If you have historical data available, Crystal Ball’s distribution fitting
feature can substantially simplify the process of selecting a probability
distribution. Not only is the process simplified, but the resulting
distribution more accurately reflects the nature of your data than if
the shape and parameters of the distribution were estimated.
How distribution fitting works
Glossary Term:
goodness-of-fit—
A set of mathematical
tests performed to find
the best fit between a
standard probability
distribution and a data
set’s distribution.
In distribution fitting, Crystal Ball automatically matches your data
against each continuous probability distribution. A mathematical fit is
performed to determine the set of parameters for each distribution
that best describe the characteristics of your data. The quality or
goodness of each fit is judged using one of several standard goodnessof-fit tests. The distribution with the highest ranking fit is chosen to
represent your data.
You can review the distributions sorted in order of their fit tests using
the comparison chart. This chart shows the fitted distributions
superimposed over your data so you can visually check the quality of
the fits. Several chart preferences make it easier to pinpoint
discrepancies in the fits. If desired, you can override the highestranking probability distribution with another one of your choice.
Crystal Ball Note: Only continuous distributions are considered for
distribution fitting. Continuous and discrete distributions are defined on
page 245. Distribution fitting can also be used to check the characteristics of a
forecast chart. See “Fitting a distribution to a forecast” on page 120 for more
information.
Use the Fit Distribution dialog to specify the source of your data, the
distributions to be fitted, and the goodness-of-fit test to use. Each
goodness-of-fit test is calculated for every distribution, but only the
selected test determines how the distributions are ranked.
Using distribution fitting
To use distribution fitting:
1. Select the cell where you want to create an assumption.
It can be blank or contain a simple value, not a formula.
2. Choose Define > Define Assumption.
The Distribution Gallery appears.
Crystal Ball User Manual
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