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