Simple and Multiple Regression Models
Abstract
This chapter presents the simple and multiple linear regression models, establishing the circumstances upon which they can be used. The parameters of the simple and multiple regression models are estimated by the least squares method and the model presuppositions are analyzed by means of tests and specific statistics. For the effect of forecast, confidence intervals of the model parameters are prepared. Nonlinear regression models are also specified, as well as the definition of the best functional form and the Box-Cox transformation. Finally, regression models are estimated in Microsoft Office Excel®, Stata Statistical Software®, and IBM SPSS Statistics Software®, and their results ...
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