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IBM® SPSS® Regression enables you to predict categorical outcomes and apply a wide range of nonlinear regression procedures.
You can apply IBM SPSS Regression to many business and analysis projects where ordinary regression techniques are limiting or inappropriate: for example, studying consumer buying habits or responses to treatments, measuring academic achievement, and analyzing credit risks.
IBM SPSS Regression includes the following procedures:
Multinomial logistic regression: Predict categorical outcomes with more than two categories
Binary logistic regression: Easily classify your data into two groups
Nonlinear regression and constrained nonlinear regression (CNLR): Estimate parameters of nonlinear models
Weighted least squares: Gives more weight to measurements within a series
Two-stage least squares: Helps control for correlations between predictor variables and error terms
Probit analysis: Evaluate the value of stimuli using a logit or probit transformation of the proportion responding
Operating systems supported: Windows, Mac, Linux
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