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Linear Models: Correlation & Regression (453-0-20)


John Michael Bailey

Meeting Info

Technological Institute LG66: Tues, Thurs 6:00PM - 7:20PM

Overview of class

This course will focus on the relatively basic linear models of univariate correlation and regression and multivariate techniques such as multiple regression, ANOVA and ANCOVA. I will give special attention to computing, interpreting, and reporting, interactions in a regression framework. The approach will be conceptual; it is my aim to take the middle ground between a more mathematically rigorous course which you might find in the Mathematics Department (or some of the more statistically-oriented courses in our department, such as those offered by Professor Bill Revelle) and a mere "cookbook" course. The primary aim is to convey a conceptual understanding, not to memorize formula or to provide rigorous proofs. There will be no matrix algebra, for example. I also want you to get a good idea how these techniques are used and reported in academic research.

Registration Requirements

Enrollment Requirements: Pre-requisite: Graduate students from any school may enroll. Undergraduates must obtain permission of the instructor.

Evaluation Method

Grading: Your grade will reflect performance on homework, a final exam, and a final data analysis project.

Lectures: This course will be taught in the classroom via lectures. In addition, I will make available some prior online lectures.

Class Materials (Required)

Textbook: Data Analysis: A Model Comparison Approach (3ndedition) by Judd, McClelland, & Ryan:

You should read along in the textbook, which is excellent.I will try to give you an idea what to read, but it's not that hard to figure out. You should read the textbook!

Computer Software: The software program JMP is required-you must use it for your homework. The program is free to NU students, here:

Enrollment Requirements

Enrollment Requirements: Pre-requisite: Student must be part of the Psychology PhD program to enroll.