Chelsea Parlett-Pelleriti

Chelsea Parlett-Pelleriti | Hands-on ways to remotely teach data science are invaluable | RStudio

Full title: With more learning occurring virtually or in hybrid mode, hands-on ways to remotely teach data science are invaluable

With more learning occurring virtually or in hybrid mode, hands-on ways to remotely teach DS are invaluable. Guided simulation exercises in R allow learners to explore concepts deeply, on their own time, and with others. They can also experiment with the simulations, try out edge cases, and challenge their assumptions, leading to more fruitful discussions. The comparison between coefficient estimates in regular, LASSO, and RIDGE regression, or how PCA performs when data are related are great examples of concepts where guided simulations can encourage learners to build intuitive knowledge. This talk explores how to use simulation exercises in R to help learners explore DS concepts and provides examples.

About Chelsea: Chelsea Parlett-Pelleriti is a PhD Candidate and full-time instructional faculty teaching Data Science at Chapman University. Her research centers around how we can use statistics and machine learning to improve the way we analyze behavioral data. In her free time, you can find Chelsea on Twitter making stats memes or statsTikTok’s. She also writes about statistics, machine learning, and using R for various blogs