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Textbook and Course Outline

The textbook is STAT2: Building Models for a World of Data, by Ann Cannon, et al. We will begin with a review of basic concepts that you should be familiar with from your intro course (Chapter 0 in the book). Next we will spend at least half the semester discussing linear regression, where the response/outcome/target variable is quantitative. This corresponds to Theme A in the book, although we will digress to Chapter 5, before returning to Chapters 3 and 4, in order to see how the Analysis of Variance (ANOVA) model can be interpreted as a form of linear regression. Next we will discuss the Analysis of Variance in detail, addressing cases with multiple explanatory/predictor variables, and connecting the statistical models to the design of experiments. This corresponds to Theme B. We will spend the last two or three weeks on Logistic Regression (Theme C), which will allow us to model binary response variables with categorical or quantitative explanatory variables. For a more detailed (tentative) schedule, see the course website (link at the top of this syllabus).

Like STAT 113/114, this is a statistics course, not a math course, and the focus will be on statistical reasoning, and the use and interpretation of statistical models, not on their mathematical derivations. Some of the mathematical detail will be glossed over, and we will rely on software to do the nitty gritty calculations. Effective use of the computer is an indispensible skill for doing statistics in the 21st century, and constitutes an important part of the course.


next up previous
Next: Computing Up: Course Description Previous: Prerequisites / Who This
Colin Dawson 2016-02-01