Stats for Informatics:
Data Science exercises

Mick McQuaid



Data Science

A classic intro textbook, James et al. (2021)

pause for exercises


What have you learned?

Four things you can do

  • Summarize numbers (tables and summaries)
  • Visualize numbers (bar charts, scatter plots)
  • Make predictions from data (linear regression, logistic regression)
  • Diagnose the quality of those predictions (plots of residuals)

Course evals

Please use the open-ended question(s) to let me know (among other things) whether you would prefer a study-guide approach to lecture as I’ve taken most of this semester, or a slideshow approach (such as I did today), where I say less explicit stuff in lecture and you look up more in the textbook for exercise completion.

So please say whatever you were going to say anyway, but also address the study-guide vs slideshow approach.


James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2021. An Introduction to Statistical Learning. Springer New York.



This slideshow was produced using quarto

Fonts are League Gothic and Lato