Science - Course - Applied Regression Analysis

This course offers a practically oriented introduction into regression modeling methods. Topics: Statistical Models and Social Science, What Is Regression Analysis?, Univariate Displays, The Family of Powers and Roots, Linear Least-Squares Regression, Simple Regression, Multiple Regression, A Dichotomous Factor, One-Way Analysis of Variance, Two-Way Analysis of Variance, Higher-Way Analysis of Variance, Analysis of Covariance, Statistical Theory for Linear Models, Simple Regression, Multiple Regression, Unusual and Influential Data, Non-Normally Distributed Errors, Detecting Collinearity, Logit and Probit Models for Categorical Response Variables, Generalized Linear Models, Polynomial Regression, Nonparametric Simple Regression: Scatter plot Smoothing. Textbook: Fox (2008): Applied Regression Analysis and GLMs. Pre-req: STAT603.