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Regression I – Introduction

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Further and more detailed information, including the schedule, can be found in the current course tables in the syllabus of the respective course, if the course is offered in the next sessions. The following text serves as information on what can be expected in terms of content in the course.

The primary goal is to develop an applied and intuitive (as opposed to purely theoretical or mathematical) understanding of the topics and procedures. Whenever possible presentations will be in “Words,” “Picture,” and “Math” languages in order to appeal to a variety of learning styles. Some more advanced regression topics will be covered later in the course, but only after the introductory foundations have been established. We will begin with a quick review of basic univariate statistics and hypothesis testing. After that we will cover various topics in bivariate and then multiple regression, including: • Model specification and interpretation. • Diagnostic tests and plots. • Analysis of residuals and outliers. • Transformations to induce linearity. • Interaction (“Multiplicative”) terms. • Multicollinearity. • Dichotomous (“Dummy”) independent variables. • Categorical (e.g., Likert scale) independent variables.