Statistical Computing: Fall 2015

Statistics 36-350

Instructor: Ryan Tibshirani (ryantibs at cmu dot edu)

Associate instructor: Ross O'Connell (rcoconne at andrew dot cmu dot edu)

TAs:
Yo Joong Choe (yjchoe at cmu dot edu)
Bryan Hooi (bhooi at andrew dot cmu dot edu)
Sangwon Hyun (shyun at cmu dot edu)
Kevin Lin (kevinl1 at andrew dot cmu dot edu)
Taylor Pospisil (tpospisi at andrew dot cmu dot edu)

Lecture times: Mondays and Wednesdays 11:30am-12:20pm, Baker Hall A51

Lab times: Fridays 10:30-11:30am in Baker Hall 140D, 140E, 140F; and 11:30am-12:20pm in Cyert Hall 100A

Office hours:
RT: Mondays 12:30-1:30pm, Baker Hall 229B
RO: Wednesday 10-11am, Wean Hall 7404
YC: Tuesday 1-2pm, Porter Hall 117
BH: Wednesday 5-6pm, Porter Hall 117
SH: Mondays 1:30-2:30pm, Baker Hall 132M

Recitations: Mondays 4-5pm in Wean 5302; Thursdays 10-11am in Hunt Library Cluster

Syllabus: here. Textbook: The R Cookbook by Paul Teetor

Discussions: Class discussions will be run through Piazza, linked here

Class schedule

Week 1: Mon Aug 31 -- Fri Sept 4. Data types and structures.

Monday:
- Intro and basics: slides, or html, pdf, Rmd
- R example: darts.R, requires the R package: darts
- Reading for the week: Chapters 2, 5; optional reading: Chapter 1
Wednesday:
- More data structures: slides, or html, pdf, Rmd
- Homework 1 assigned: html, pdf, Rmd; data: strike.txt
Friday:
- Lab 1: html, pdf, Rmd
Week 2: Mon Sept 7 -- Fri Sept 11. More data structures.

Monday: no class

Wednesday:
- More data structures (continued from last lecture)
- Reading for the week: Chapter 5 (re-read it)
- Homework 1 due. Homework 2 assigned: html, pdf, Rmd
Friday:
- Lab 2: html, pdf, Rmd
Week 3: Mon Sept 14 -- Fri Sept 18. Data frames and flow control.

Monday:
- Data frames and flow control slides, or html, pdf, Rmd
- Reading for the week: Chapter 5 (especially parts on data frames), and the R Cookbook has nothing on flow control, so e.g., you could read the R help file on the topic (type `?Control` in R console)
Wednesday:
- Data frames and flow control (continued from last lecture)
- Homework 2 due. Homework 3 assigned: html, pdf, Rmd
Friday:
- Lab 3: html, pdf, Rmd
Week 4: Mon Sept 21 -- Fri Sept 25. Text.

Monday:
- Text basics: slides, or html, pdf, Rmd
- Reading for the week: Chapter 7 (don't worry about the parts on dates), and the R Cookbook has nothing on regular expressions, but there are many online tutorials, e.g., http://www.zytrax.com/tech/web/regex.htm
- Recitation for the week: html, pdf, Rmd
Wednesday:
- Regular expressions: slides, or html, pdf, Rmd
- Homework 3 due. Homework 4 assigned: html, pdf, Rmd
Friday:
- Lab 4: html, pdf, Rmd
Week 5: Mon Sept 28 -- Fri Oct 2. Functions.

Monday:
- Functions: slides, or html, pdf, Rmd
- Reading for the week: the R Cookbook has little on writing functions, but you can find a bit in Chapter 2.12
- Recitation for the week: html, pdf, Rmd
Wednesday:
- Functions (continued from last lecture)
- Homework 4 due. Homework 5 assigned: html, pdf, Rmd
Friday:
- Lab 5: html, pdf, Rmd
Week 6: Mon Oct 5 -- Fri Oct 9. Getting data and fitting models.

Monday:
- Getting data: slides, or html, pdf, Rmd
- Reading for the week: Chapters 4, 11 (don't worry about the parts on MySQL or ANOVA)
- Recitation for the week: html, pdf, Rmd
Wednesday:
- Fitting data: slides, or html, pdf, Rmd
- Homework 5 due. **Midterm exam assigned**: html, pdf, Rmd, and midterm-pairings.html
Friday:
- Lab 6: html, pdf, Rmd
Week 7: Mon Oct 12 -- Fri Oct 16. Transformations and debugging.

Monday:
- Transformations: slides, or html, pdf, Rmd
- Reading for the week: Chapters 6, 12 (through 12.13)
- Recitation for the week: html, pdf, Rmd
Wednesday:
- Debugging: slides, or html, pdf, Rmd
- **Midterm in progress**, no new homework
Friday:
- Lab 7: html, pdf, Rmd
Week 8: Mon Oct 19 -- Fri Oct 23. Testing and design.

Monday:
- Debugging (continued from last lecture)
Wednesday:
- Design: slides, or html, pdf, Rmd
- **Midterm due**. Homework 6 assigned: html, pdf, Rmd
Friday: no lab
Week 9: Mon Oct 26 -- Fri Oct 30. More functions, optimization.

Monday:
- More functions, optimization: slides, or html, pdf, Rmd
Wednesday:
- More functions, optimization (continued from last lecture)
- Homework 6 due. Homework 7 assigned: html, pdf, Rmd
Friday:
- Lab 8: html, pdf, Rmd
Week 10: Mon Nov 2 -- Fri Nov 6. Optimization.

Monday:
- Optimization: slides, or html, pdf, Rmd
- Optional reading for the week: you can browse through the class slides for our graduate course on Convex Optimization, here
Wednesday:
- Optimization (continued from last lecture)
- Homework 7 due. Homework 8 assigned: html, pdf, Rmd
Friday:
- Lab 9: html, pdf, Rmd
Week 11: Mon Nov 9 -- Fri Nov 13. Split-apply-combine.

Monday:
- Split-apply-combine: slides, or html, pdf, Rmd
Wednesday:
- Better apply functions: slides, or html, pdf, Rmd
- Homework 8 due. Homework 9 assigned: html, pdf, Rmd
Friday:
- Lab 10: html, pdf, Rmd
Week 12: Mon Nov 16 -- Fri Nov 20. More split-apply-combine and databases.

Monday:
- More split-apply-combine: slides, or html, pdf, Rmd
Wednesday:
- Databases: slides, or html, pdf, Rmd
- Optional reading on databases: you can read through this handout from last year's Statistical Computing course, here
- Homework 9 due. **Final exam assigned**: html, pdf, Rmd, and final-pairings.html. Also, see bonus problem: html, pdf, Rmd
Friday:
- Lab 11: html, pdf, Rmd
Week 13: Mon Nov 23 -- Fri Nov 27. More databases.

Monday:
- More databases: slides, or html, pdf, Rmd
Wednesday: no class
- **Final exam in progress**, no new homework
Friday: no lab
Week 14: Mon Nov 30 -- Fri Dec 4. Simulation.

Monday:
- Simulation: slides, or html, pdf, Rmd
- Optional reading for the week: you can browse through this paper
Wednesday:
- Simulation: slides, or html, pdf, Rmd
- **Final exam in progress**, no new homework
Friday:
- Lab 12: html, pdf, Rmd
Week 15: Mon Dec 7 -- Fri Dec 11. Final exam week.

Monday: no class
- **Final exam due**
Wednesday: bonus competition

Friday: no class

Top

Credit where credit is due

This course closely follows Cosma Shalizi's previous versions of the course.

Top

Supplementary materials

Supplementary textbooks on R programming:

The Art of R Programming: A Tour of Statistical Software Design, by Norman Matloff
Data Manipulation with R, by Phil Spector
The R Graphics Cookbook, by Winston Chang
Software for Data Analysis: Programming with R, by John Chambers (advanced book)

Online resources for R programming:

The official intro, "An Introduction to R", available online in html and pdf versions
simpleR, by John Verzani
Google R Style Guide offers some rules for naming, spacing, etc., which are generally good ideas
Quick-R, this is primarily aimed at those who already know a commercial statistics package like SAS, SPSS or Stata, but it's very clear and well-organized, and others may find it useful as well
The R Inferno, by Patrick Burns ("If you are using R and you think you're in hell, this is a map for you")
R Fundamentals and Programming Techniques, by Thomas Lumley

The website Software Carpentry is not specifically R related, but contains a lot of valuable advice and information on scientific programming.

Top