Interpreting and Communicating Statistical Results with R: A Short Course

A 3-Day Livestream Seminar Taught by Vincent Arel-Bundock, Ph.D.

Check out the marginaleffects and modelsummary packages in more detail on Vincent’s website here!

This seminar is designed to help you tackle the challenges of understanding and conveying complex statistical results. Coefficient estimates can often be difficult to interpret, and their substantive meaning are not always obvious. This course provides you with the tools and knowledge to overcome these obstacles, making it easier for you to present your findings with clarity and confidence.

Throughout the course, we’ll teach you an easy, consistent, and flexible approach to interpreting a wide range of statistical models in R. You’ll gain a deep understanding of statistical concepts such as predictions, contrasts, marginal means, marginal effects, odds ratios, and risk ratios. The course will introduce you to a powerful toolkit in R, specifically designed to compute and report the most appropriate quantities of interest for your use case.

To reinforce your learning, the course will include hands-on exercises that allow you to apply these concepts in real-world scenarios. By learning how to generate plots and tables to illustrate your findings and create reproducible reports, you’ll be able to convey your results effectively to your audience and stakeholders, even when dealing with intricate models.

Starting November 16, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. 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.

*We understand that finding time to participate in livestream courses can be difficult. 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 four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.

Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.

More Details About the Course Content

By the end of this class, you’ll be well-equipped to not only make sense of complex statistical results but also to communicate them in a compelling and engaging manner, ensuring that your research or work has a lasting impact. With a comprehensive understanding of the distinctions between various statistical concepts and the ability to apply an advanced toolkit in R, you’ll be prepared to tackle statistical challenges with confidence.

The course content includes:

    • Clarifying distinctions between statistical concepts such as predictions, contrasts, marginal means, marginal effects, odds ratios, and risk ratios.
    • Introducing a powerful toolkit in R to compute and report the most appropriate quantities of interest for your use case.
    • Generating plots and tables to illustrate your findings.
    • Creating reproducible reports and slideshows for stakeholders.

You will also be introduced to several useful R packages, including:

Who Should Register?

This course is for anyone who wants to leverage the power of statistical models to deliver clear, compelling insights. If you are a data analyst, researcher, statistician, or data-driven professional who often needs to interpret complex statistical models and communicate findings in an intuitive, comprehensible manner, this course is for you.

While the course is designed to be broadly accessible, the instructor will assume that you have a working knowledge of R programming (at the level of our Statistics with R course or its equivalent) and linear regression models. A basic understanding of generalized linear models would also help you get the most out of the course, but it is not essential.


To participate in the hands-on exercises, you are strongly encouraged to use a computer with the most recent version of R installed, together with the tidyverse, marginaleffects, modelsummary, and gt libraries. You are also encouraged to download and install RStudio, a front-end for R that makes it easier to work with. This software is free and available for Windows, Mac, and Linux platforms. Basic familiarity with R is highly desirable, but even novice R coders should be able to follow the presentation and do the exercises.

If you’d like to take this course but are concerned that you don’t know enough R, there are excellent on-line resources for learning the basics. Here are our recommendations.


  1. The programming environment
    • R
    • Rstudio
    • Quarto
    • R Libraries
      • Modelling: MASS
      • Interpretation: marginaleffects
      • Communication: modelsummary, gt
  1. Statistical building blocks
    • Predictions
    • Comparisons
    • Slopes
    • Hypothesis tests
  1. Interpretation
    • Using the marginaleffects package to compute quantities of interest
  1. Communication: Plots, tables, and reports
    • marginaleffects
    • modelsummary
    • Quarto

Seminar Information

Thursday, November 16 –
Saturday, November 18, 2023

Daily Schedule: All sessions are held live via Zoom. All times are ET (New York time).

10:00am-12:30pm (convert to your local time)

Payment Information

The fee of $995 includes all course materials.

PayPal and all major credit cards are accepted.

Our Tax ID number is 26-4576270.