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R Programming
R Programming
  • Syllabus
  • Schedule
  • Readings
  • Classes
  • Functions
  • Midterm Projects
  • Course Reviews
Reading details
  • Reading policy
Readings
  • Part 1: Introduction to R/RStudio/Vectors/
  • Part 2: Data Frames/Loading Data/ggplot2
  • Part 3: `ggplot2`, factors, boxplots, `dplyr`: subsetting using `filter()`/`select()`
  • Part 4. `dplyr`: `mutate()`, `group_by()`/`summarize()`/`across`
  • Part 5. More about manipulating factors (`forcats`)/doing things with multiple tables/functions()
  • Part 6. Lists and RMarkdown
  • Part 7. purrr
  • Part 8. Statistical Modeling/More purr
  • Part 9. Tidymodels/Unsupervised Learning/Logistic Regression
  • Part 10. Tidymodels/Supervised Learning/Logistic Regression

Part 8. Statistical Modeling/More purrr

Required

  • Model Basics from R for Data Science
  • Model Building from R for Data Science
  • Many Models - from R for Data science. Covers group_by()/nest() and list-columns
  • Purrr Tips and Tricks by Emil Hvitfeldt.

Last updated on February 25, 2021

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BSTA 504: R Programming (Winter 2021)
Oregon Health & Science University / Portland State University    OHSU/PSU School of Public Health

Dr. Ted Laderas    laderast@ohsu.edu

Wednesdays    3:15–6:05 PM
Online

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