MATERIAL
Applied computational statistics for analytics
Lectures
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.
Textbook
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!
Software
Other
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:
A site with various tutorials on R and statistics
MIT Open Courseware on Python
Learn R in 15 minutes from Prof. Yang at UIC (visit this page with so many more links, too!)
Stats refreshers:
A lovely (and pretty complete?) list of resources for learning R: