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## General linear modeling course

This is the first semester of a two semester graduate statistics sequence. The sequence covers ANOVA and regression in the fall term and multivariate techniques, including basic structural equation modeling, in the winter term. You should plan on taking both courses. Taking only Psychology 613 wouldn’t make much sense, and I rarely let students in Psychology 614 who have not also taken Psychology 613.

This course emphasizes practical techniques for analyzing data and developing intuition for understanding the techniques used in Psychology. I do not cover the mathematics of the relevant statistical theory. If you are interested in the mathematical detail, you should consider taking courses in the statistics department. Keep in mind that a solid background in calculus, linear algebra, real analysis, etc., may be needed to excel in a more mathematically-oriented statistics course. This possibility should be discussed with the individual student.

Here is a syllabus from the last time I taught this course.

The lecture notes for this course are posted here. I typically finish the fall term with lecture notes #8.

** Background for Psychology 613**

Entering students ask how they can prepare for the first year statistics sequence. A good strategy is to review your notes from an undergraduate statistics course, or work through an undergraduate statistics book over the summer. You should be familiar with measures of central tendency (means, medians), measures of variability (variance, interquartile range), graphical devices (boxplot, scatterplot), the logic of hypothesis testing, the notion of a confidence interval, and details surrounding one and two-sample t-tests. The year-long statistics sequence is self-contained, but I do assume that you know these basic topics so come prepared to the first lecture.

Some of you may benefit from taking a background course the summer before your first year in graduate school. One possibility is to take a summer course through ICPSR. Probably the most relevant preparation courses are Introduction to Statistics and Data Analysis I.