OPEN SCIENCE

I believe good science can only be built on the principles of open science, diverse and inclusive teamwork, and good leadership. At the MPI, I am one of two Open Science Ambassadors.

It’s important to me to share my materials, code, and resources with the community. I share my analysis code and any available anonymized data on my OSF (Open Science Foundation) page.

Below, you’ll find free materials I’ve created for teaching statistics, with links to Youtube videos and exercises.

Click here for my OSF

LEARN STATS: MATERIALS

Check out the five part introductory series I co-organized several years ago:
- Part 1 - Intro to R and R-Markdown: Video, Exercise
- Part 2 - Tidy Data: Video, Exercise
- Part 3 - Data Wrangling with dplyr: Video, Exercise
- Part 4 - Data Visualization with ggplot: Video, Exercise
- Part 5 - Advanced Wrangling: Video, Exercise
After that, you can check out the advanced ggplot topics like adding annotations, using custom fonts, using custom color schemes, and editing details in theme().
And similar videos on linguistic data can be found in this playlist.
You can also download the guide to R that I made for MPI interns here.
Running linear mixed effects models in Julia allows you to harness the power of this new(er) programming language, while packages that integrate R functionality make the learning curve super easy.
Check out my materials and code on this topic here.
Text analysis is also easy in R, check out my videos on the topics of:
- Tidy text analysis: Word frequencies and n-grams, Video
- Sentiment analysis, Video
Want to make interactive dashboards? Check out my video on using Shiny for online applications in R here.
Another package I use all the time is gt, for creating publication-level charts with ggplot-like syntax. Video here.

Data Wrangling and Visualization in R

Mixed Effects Models in R & Julia

Text Analysis

Other Topics

kyla.mcconnell {at} mpi {dot} nl