On many occasions, it is appropriate to use a simple linear model to regress data. On other occasions, however, such as when the dependent variable is a probability, transformed linear combinations of the independent variables so that their values are contained within the interval [0,1]. This Demonstration takes 10 sample datasets and compares a simple linear regression to two frequently used alternatives: the probit model and the logit model. The fitting used assumes normally distributed residuals. You select the dataset, the regression model you wish to examine, and the set of regression report items you wish to see.
