Statistical Computing: Fall 2019

Statistics 36-350 Instructor: Ryan Tibshirani (ryantibs at cmu dot edu) Important note: please direct emails on all course related matters to the Head TA, not the Instructor. The subject line of all emails should begin with "[36-350]". Head TA: Theresa Gebert (tgebert at andrew dot cmu dot edu) TAs: Irina Javed (irjaved at andrew dot cmu dot edu) Long Jiang (longj1 at andrew dot cmu dot edu) Undergrad TAs: Sasha Cohen-Ionnides (scohenio at andrew dot cmu dot edu) Sana Lakdawala (slakdawa at andrew dot cmu dot edu) Filipp Shelobolin (fshelobo at andrew dot cmu dot edu) Class times: Mondays, Wednesdays, and Fridays 11:30am-12:20pm, Baker Hall 136A Office hours: RT: Mondays 3:00-4:00pm, Baker 229B TG: by request IJ: Thursdays 1:30-2:30pm, Baker 237B LJ: Fridays 2:00-3:00pm, Baker 132Q FS+SL: Sundays 3:00-4:00pm, Gates cafe Syllabus: here. Discussions: Piazza group.

Class schedule

• Week 1 (Mon Aug 26 - Fri Aug 30). Basic data structures.
  
  
  • Notes: slides, html, Rmd
    
  • Intruder code: intruder_demo.R, intruder.R
  • Quiz 1 (see Canvas)
  • Lab 1: html, Rmd
• Week 2 (Wed Sept 4 - Fri Sept 6). Indexing and iteration.
  No class Monday: Labor Day.
  
  
  • Notes: slides, html, Rmd
  • Quiz 2: (see Canvas)
  • Lab 2: html, Rmd
• Week 3 (Mon Sept 9 - Fri Sept 13). Data frames and apply.
  
  
  • Notes: slides, html, Rmd
  • Plyr (optional): slides, html, Rmd
  • Quiz 3: (see Canvas)
  • Lab 3: html, Rmd
• Week 4 (Mon Sept 16 - Fri Sept 20). Text manipulation.
  
  
  • Notes: slides, html, Rmd
  • Quiz 4: (see Canvas)
  • Lab 4: html, Rmd
• Week 5 (Mon Sept 23 - Fri Sept 27). Plotting.
  
  
  • Notes: slides, html, Rmd
  • Quiz 5: (see Canvas)
  • Lab 5: html, Rmd
• Week 6 (Mon Sept 30 - Fri Oct 4). Functions.
  
  
  • Notes: slides, html, Rmd
  • Quiz 6: (see Canvas)
  • Lab 6: html, Rmd
• Week 7 (Mon Oct 7 - Fri Oct 11). Simulations.
  
  
  • Notes: slides, html, Rmd
  • Quiz 7: (see Canvas)
  • Lab 7: html, Rmd
• Week 8 (Mon Oct 14 - Wed Oct 16). Reading in data.
  No class Friday: Midsemester break.
  
  
  • Notes: slides, html, Rmd
  • Quiz 8: (see Canvas)
  • Lab 8: html, Rmd
• Week 9 (Mon Oct 21 - Wed Oct 23). Fitting models to data.
  No class Friday: Community Engagement Day.
  
  
  • Notes: slides, html, Rmd
  • Quiz 9: (see Canvas)
  • Lab 9: html, Rmd
• Week 10 (Mon Oct 28 - Fri Nov 1). Tidyverse I: Pipes and dyplr.
  
  
  • Notes: slides, html, Rmd
  • Quiz 10: (see Canvas)
  • Lab 10: html, Rmd
• Week 11 (Mon Nov 4 - Fri Nov 8). Tidyverse II: Tidyr and more dyplr.
  
  
  • Notes: slides, html, Rmd
  • Quiz 11: (see Canvas)
  • Lab 11: html, Rmd
• Week 12 (Mon Nov 11 - Fri Nov 15). Debugging and testing.
  
  
  • Notes: slides, html, Rmd
  • Quiz 12: (see Canvas)
  • Lab 12: html, Rmd
• Week 13 (Mon Nov 18 - Fri Nov 22). Relational databases.
  
  
  • Notes: slides, html, Rmd
  • Quiz 13: (see Canvas)
  • Lab 13: html, Rmd
• Week 14 (Mon Nov 25). Versional control and git.
  No class Wednesday and Friday: Thanksgiving!
  
  
  • Notes: slides, html, Rmd
  • Quiz 14: (see Canvas)
  • No lab!
• Week 15 (Mon Dec 2 - Fri Dec 6). Statistical prediction.
  Final exam on Friday.
  
  
  • Notes: slides, html, Rmd
  • No quiz!
  • Lab 14: html, Rmd

Supplementary materials

• The R Cookbook, by Paul Teetor
• The R Graphics Cookbook, by Winston Chang
• The Art of R Programming: A Tour of Statistical Software Design, by Norman Matloff
• Data Manipulation with R, by Phil Spector
• Software for Data Analysis: Programming with R, by John Chambers (advanced book)
• R for Data Science, by Hadley Wickham (based in tidyverse)

• The official intro, "An Introduction to R", available online in html and pdf versions
• simpleR, by John Verzani
• R Fundamentals and Programming Techniques, by Thomas Lumley
• Google's R Style Guide offers guidelines for naming, spacing, etc.
• RStudio Cheat Sheets, quick reference guides for many common packages