Introduction to Regression and Linear Models

Catalog description

Covers the general linear model as a data analytic framework through which applications such as correlation, multiple regression and analysis of variance can be carried out to address predictive research questions frequently posed by behavioral and social scientists. Also teaches practical applications of data analysis with real data issues, covering topics such as power analysis and sample size planning, data transformation and dealing with data nonlinearity and nonnormality.