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SAS/INSIGHT User's Guide |

Choosing **Analyze:Fit ( Y X )** gives you access to
a variety of techniques for fitting models to data.
These provide methods for examining the relationship
between a response (dependent) variable and a set of
explanatory (independent) variables.
You can use least-squares methods for simple and multiple
linear regression with various diagnostic capabilities
when the response is normally distributed.
You can use generalized linear models to analyze the data
when the response is from a distribution of the exponential
family and a function can be used to link the response mean
to a linear combination of the explanatory variables.
You can use spline and kernel smoothers for nonparametric
regression when the model has one or two explanatory variables.

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