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Livestream Seminar

Logistic Regression

A 3-Day Livestream Seminar Taught by

Paul Allison
Course Dates: Ask about upcoming dates
Schedule: All sessions are held live via Zoom.

10:00am-2:00pm ET (New York time): Live lecture via Zoom
4:00pm-5:00pm ET: Live lab session via Zoom (Thursday and Friday only)

Logistic regression is by far the most widely used statistical method for the analysis of categorical data. In this seminar, you’ll learn virtually everything you need to know to become a skilled user of logistic regression. We’ll cover the theory and practice of binary logistic regression in great detail including topics such as:

  • odds and odds ratios
  • maximum likelihood estimation
  • interpretation of coefficients
  • convergence failures
  • goodness of fit
  • contingency table analysis
  • response-based sampling

Starting April 22, we are offering this seminar as a 3-day synchronous*, remote workshop for the first time. Each day will consist of a 4-hour live lecture held via the free video-conferencing software Zoom. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

Each lecture session will conclude with a hands-on exercise reviewing the content covered, to be completed on your own. An additional lab session will be held Thursday and Friday afternoons, where you can review the exercise results with the instructor and ask any questions.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for two weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.

More details about the course content

Computing

Who should register?

Seminar outline

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“The Logistic Regression course gave me in-depth hands-on experience..."

“The Logistic Regression course gave me in-depth hands-on experience. I wish the class could have been longer!”

Lora Kasselman

City University of New York

"I would definitely recommend this course..."

“For a person with little background in Stata and very little knowledge about SAS, I think this course is relatively easy to follow. The booklet provided different examples and helped a lot in understanding the course. I would definitely recommend this course to those who just started to explore the data analysis field.”

Hoi Ting Wan (Cheryl)

Northwestern University

“Dr. Paul Allison is a tremendous instructor..."

“Dr. Paul Allison is a tremendous instructor and very clear in his teaching style. I found the Logistic Regression course built off of other statistical training and extended my understanding of analyses using categorical data.”

Andrea Johnson

Georgetown University

"I loved the time to actually work on Stata during the course..."

“I have attended several statistics courses in school and online courses but this course really clarified my concepts like no other. I loved the time to actually work on Stata during the course so that there was an opportunity for asking questions in real time. I would highly recommend this course!”

Shweta Gore

MGH Institute of Health Professions

"... this course was a good introduction to the real application..."

“As a master’s student, this course was a good introduction to the real application of advanced statistical methods in complex analysis. The course investigated the inherent messiness of data, generating solutions to overcome any problems associated with them.”

Nicholas Bernardo

University of Rhode Island

“The course is exactly what I need to have a clear understanding of logistic regression..."

“The course is exactly what I need to have a clear understanding of logistic regression. I’ve learned many useful commands to analyze the data. I’ve also learned how to precisely interpret the data. The instruction is clear, hands-on, with lots of useful tips and examples. Highly recommended for anyone who wants to have a thorough understanding of logistic regression.”

Xiaoli Yin

Baruch College