August Member Training: Explaining Logistic Regression Results to Non-Researchers

by TAF Support

Interpreting the results of logistic regression can be tricky, even for people who are familiar with performing different kinds of statistical analyses. How do we then share these results with non-researchers in a way that makes sense?

In this training we will:

  • Review logistic regression
  • Discuss numerical ways to interpret:
    Coefficients for numeric and categorical variables
    Comparisons among groups
    Interactions
  • Examine graphical ways to describe results

This webinar is appropriate for those with some experience with logistic regression, but as long as you are familiar with linear regression you will be able to follow most of it.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.


Date and Time

Wednesday, August 26th, 2020
1:00pm-2:30pm (America/New_York)
In a different time zone?

About the Instructor

Kim is a workshop instructor for The Analysis Factor and owner/lead consultant at K.R. Love Quantitative Consulting and Collaboration.

She has worked as a statistical consultant and collaborator in multiple professional roles, most recently as the associate director of the University of Georgia Statistical Consulting Center.

Kim has more than a decade of professional and academic experience in the fields of regression and linear models, categorical data, generalized linear models, mixed effects models, nonlinear models, repeated measures, and experimental design. She has a B.A. in mathematics from the University of Virginia, and an M.S. and PhD in statistics from Virginia Tech.

Not a Member Yet?

It’s never too early to set yourself up for successful analysis with support and training from expert statisticians. Just head over and sign up for Statistically Speaking. You'll get access to this training webinar and 85+ other stats trainings — plus the expert guidance you need to progress with live Q&A sessions and an ask-a-mentor forum.

Binary, Ordinal, and Multinomial Logistic Regression for Categorical Outcomes
Get beyond the frustration of learning odds ratios, logit link functions, and proportional odds assumptions on your own. See the incredible usefulness of logistic regression and categorical data analysis in this one-hour training.

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