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Linear Regression - Online Course

A 4-Week On-Demand Seminar Taught by

Paul Allison
Course Dates: Ask about upcoming dates

Each Monday you will receive an email with instructions for the following week.
All course materials are available 24 hours a day. Materials will be accessible for an additional 2 weeks after the official close on October 17.

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Linear regression is the most widely-used method for the statistical analysis of non-experimental (observational) data. It’s also the essential foundation for understanding more advanced methods like logistic regression, survival analysis, multilevel modeling, structural equation modeling, and even machine learning. Without a thorough mastery of linear regression, there’s little point in trying to learn more complex regression methods.

In this on-demand seminar, Dr. Paul Allison will teach everything you really need to know about linear regression. Based on his book Multiple Regression, the course provides a very practical, intuitive, and non-mathematical introduction to the topic.

This course takes place in a series of four weekly installments of videos, quizzes, readings, and assignments, and requires about 6-8 hours/week. You can participate at your own convenience; there are no set times when you are required to be online. The course can be accessed with any recent web browser on almost any platform, including iPhone, iPad, and Android devices. It consists of 10 modules:

  1. Introduction to Linear Regression
  2. Trivariate Regression
  3. Statistical Inference in Regression
  4. Dummy Variables and Standardized Coefficients
  5. Non-linearity
  6. Interaction
  7. Heteroscedasticity and Multicollinearity
  8. Missing Data
  9. Maximum Likelihood and Multiple Imputation
  10. Model Building and Variable Selection

The modules contain videos of the live, 2-day version of the course in its entirety. Each module is followed by a short multiple-choice quiz to test your knowledge. There are also weekly exercises that ask you to apply what you’ve learned to a real data set.

Each week, there are 2-3 assigned articles to read. There is also an online discussion forum where you can post questions or comments about any aspect of the course. All questions will be promptly answered by Dr. Allison.

Downloadable course materials include the following PDF files:

  • All slides displayed in the videos.
  • Exercises for each week.
  • Readings for each week.
  • Computer code for all exercises (in SAS, Stata, and R formats).
  • A certificate of completion.

More details about the course content


Who should register?

Registration instructions

“Excellent course, very helpful and thorough."

“Excellent course, very helpful and thorough. It helps to clarify misconceptions or “muddiest points” that you may have from previous work in statistics.”

Mariya Kovaleva

University of Nebraska Medical Center

"I now have a cheat sheet for many of these common statistical issues.”

“Thank you SO MUCH for this course – I have learned an incredible amount. The balance you struck between concepts/theory and practical application was perfect. As an applied public health researcher, I learned most of my statistical methods “on the job” and this has been a great refresher course for me. As a journal editor, I am frequently faced with debate between author and reviewer re: some of the issues you raised that are commonly misunderstood (e.g. which variables need normal distribution, whether to include original and transformed variables, etc). With the course PPT and resources, I now have a cheat sheet for many of these common statistical issues.”

Kenda Cunningham

Helen Keller International

“Fantastic course for regression beginners..."

“Fantastic course for regression beginners with some basic statistical background. The video lectures complement the readings and Stata work very well. Will take another online course from Prof. Allison for sure!”

Brian Jewett

Claremont Graduate University

"All the topics were well-explained with exercises and examples.”

“Learned in-depth details of linear regression. All the topics were well-explained with exercises and examples.”

Thilini Salpahewage

University of Canberra