BST430 - Introduction to Statistical Computing

University of Rochester, Fall 2024

Administrivia

MW 11:00-12:40, SRB 1402
Instructor: Tanzy Love
Website: https://bst-urmc.github.io/bst430-fall2024-site/
Syllabus

Content

0. Introduction
1. Meet the toolkit
   • Invites to GitHub class room are on blackboard
   • Req readings: r4ds 3.1-3.5, 4.
   • Optional readings: https://happygitwithr.com/

• Resources:
  1. install GIT
  2. install base R
  3. install RStudio
  • Lab 0 instructions and repo (accept GH classroom invite in Blackboard).

2. ggplot(i)
   • Lab 1 instructions and repo (accept GH classroom invite). Due 5pm, Sept 11.
   • Lab 1 solutions
3. dplyr(i)
   • Continue working on Lab 1
   • HW 1 assigned. instructions and repo (accept GH classroom invite). Due 5pm EDT, Sept 16.
   • HW 1 solutions
4. Data types in R.
   • Lab 2. You will need to accept the invitation. Due 5pm, Sept 18.
   • Lab 2 solutions
5. Reshaping and combining data frames.
6. Advanced dplyr(ii)
   • Lab 3. To be completed in same group as lab 2, invitation here. Due 5pm, Sep 25.
   • Lab 3 solutions
7. Factors and dates
   • Continue working on Lab 3
   • HW 2 assigned. instructions and repo (accept GH classroom invite). Due 5pm EDT, Sep 30.
   • HW 2 solutions
8. Effective data visualization (i) (ii) video
   • Turn in lab 3.
9. Data from files
   • Repository for lecture 9 here will not be graded, but gets you everything you need at once.
   • Lab 4. New groups! At least one new teammate for each person. Invitation here. Due 5pm, Oct 7.
   • Lab 4 solutions
10. styleguide
    • Finish lab 4.
11. Text processing and Regular Expressions
    • HW 3 assigned. instructions and repo (accept GH classroom invite). Due 5pm EDT, Oct 14.
    • HW 3 solutions
12. Text analysis
    • Lab 5. Pair up; you might want to take turns Pull-Committing because changing figures can cause extra GIT problems. Invitation here. Due 5pm, Oct 18.
    • Lab 5 solutions
    • Reading: r4ds chapter 14
13. Matrices, indexing, linear algebra
    • Finish Lab 5
14. Functions i.
    • Lab 6, make any groups as you like. Invitation here. Due 5pm, Oct 30.
    • Lab 6 solutions
15. Functions ii and iteration
    • HW 4 assigned. instructions and repo (accept GH classroom invite). Due 5pm EDT, Nov 4.
    • HW 4 solutions
    • Work on Lab 6
16. Knitr tricks and debugging

* Work on Lab 6

17. Linear models

* Work on Lab 6

18. Multivariate linear models

*  Work on Lab 6

19. Prediction and logistic regression
20. No class 11/6, work on your final exam.

• Final Exam. Remember I will be looking at the .md for results and the .Rmd for your code. instructions and repo (accept GH classroom invite). Due 5pm EDT, Nov 7.

21. Ensemble models extra stuff from Matt Corsetti Thesis