To keep them engaged you need some applied project work with real (although preferably pre-cleaned) data sets and a real software environment. In my college cou

To keep them engaged you need some applied project work with real (although preferably pre-cleaned) data sets and a real software environment. In my college courses I would lose focus in the lectures when equation after equation was presented and explained, but the homework projects with real data forced me to learn and internalize how to use different statistical tools (although it didn't really teach me how they are implemented). In my college econometrics courses we used Stata for this, but I'd probably recommend R if you have a choice. The book "R for Data Science"[1] is really good for teaching the basics of data manipulation, graphing, and running regressions. However, it's not a statistics book - you'd need to consider it a "supplement" to teach applied skills. You'd also want to skip the chapters that focus on cleaning data, programming, etc. [1] https://r4ds.had.co.nz/ https://r4ds.had.co.nz/