Applied computational statistics for analytics


Lectures in this course use a combination of hand-written notes and slides. As they use copyrighted material, students are not allowed to post course materials anywhere (on the internet, on their sites, in other courses, etc.). Once updated, lecture slides will be released with a link here under a Creative Commons 3.0 License; stay tuned for more info.


The material will be drawn from these primary sources:

      • An Introduction to statistical inference and its applications with R [link]

      • An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) [library link for online version]; see also [book link ]

      • Data Science Using Python and R [link]. ← log into IIT portal to access online version @Galvin!



Links to other reading materials and/or videos will be provided throughout the semester.

Software & Statistics help

New to R? New to Python? Can't remember something "basic" in stats? Just need a refresher?

Not to worry!
Writing scripts: One of our reference texts has a lot of background and examples - it builds scripts bottom-up! You can always start there. If you want to browse a few other resources, these seem excellent choices:

Stats refreshers:

  • Video lectures about basic statistical concepts

  • Intro to Statistics online at Penn State.

A lovely (and pretty complete?) list of resources for learning R: