BST430 - Introduction to Statistical Computing

University of Rochester, Fall 2021

Administrivia

MW 11:00-12:40, SRB 1402
Instructor: Andrew McDavid
Website: https://urmc-bst.github.io/bst430-fall2021-site/
Syllabus

Content

0. Introduction
   • Survey
1. Meet the toolkit
   • Invites to rstudio cloud and github class room are on blackboard
   • Req readings: r4ds 3.1-3.5, 4. Optional: https://happygitwithr.com/
2. ggplot(i)
   • CandyWeight for real.
   • Lab 1 instructions and repo (accept GH classroom invite). Due 5pm Sept 3.
3. dplyr(i)
   • Continue working on lab 1
4. Data types in R. Finish dplyr(i) lecture.
   • HW 1 assigned. instructions and repo (accept GH classroom invite). Due 5pm EDT, Sept 13.
5. Reshaping and combining data frames. Finish data types lecture.
   • Lab 2. You will need to accept an invitation to join the URMC-BST organization to get access to your repositories to complete these. Most labs will be completed in groups going forward – if you cannot attend class in person for whatever reason, let me know and I’ll set up zoom so you can participate synchronously and remotely.
6. Finish L5a.
   • Lab 3. To be completed in same group as lab 2.
7. dplyr(ii), styleguide
   • Lab 4. New groups!
8. Factors and dates
   • HW 2 assigned.
9. Effective data visualization video and slides, rstudio.cloud project and quiz.
   • Continue working on lab 4.
10. Data from files
    • Lab 5 assigned
    • Andrew’s office hours will be at 4:30 Thursday this week.
11. Work on lab 5.
12. Text processing
    • Discuss lab 5. HW 3 assigned.
    • Reading: r4ds chapter 14
13. Continue L10.
14. Matrices, indexing, linear algebra
    • Lab 6 assigned.
15. Continue with matrices / linear algebra and Lab 6.
16. Functions i, continue to work on lab6.
17. Functions ii and iteration. HW04 (Due 5PM Nov 5)
18. Knitr tricks and debugging. Lab 07 due 5PM Nov 12. Lab 07 notes.
19. Linear models
20. Multivariate linear models
21. Prediction and logistic regression
    • HW5 due 24 Nov.