On Thursday, I led a workshop on conducting synthetic data experiments (simulation studies) in R to raise money to support Ukraine. It was a lot of fun walking through what simulations studies are, why you might want to conduct one, and how to do the process from start to finish using the R simulator package. The participants did great and had great questions. I was told over 40 people registered, raising over 800 euro (around $900 at today’s exchange rate) donated directly to nonprofits supporting Ukraine.
If you’re interested in the content but you missed the workshop, you can still access the recording, slides, and code from the workshop by donating 20 euro directly to your choice of three organizations and sending the receipt to the organizer, Dariia Mykhailyshyna. See details here.
Here’s the description of the workshop from the website:
In simulation studies (also known as Monte Carlo simulations or synthetic data experiments), we generate data sets according to a prespecified model, perform some calculations on each data set, and analyze the results. Simulation studies are useful for testing whether a methodology will work in a given setting, assessing whether a model “works” and diagnosing problems, evaluating theoretical claims, and more. In this workshop, I’ll walk through how you can use the R simulator package to conduct simple, reproducible simulation studies. You’ll learn how to carry out the full process, including making plots or tables of your results.