Schedule
Schedule and course materials for Statistical Computing (JHSPH Biostatistics 140.776).
Schedule and course materials
For Qmd files (markdown document with Quarto cross-language executable code), go to the course GitHub repository and navigate the directories, or best of all to git clone the repo and navigate within RStudio.
Check https://github.com/lcolladotor/biostat776classnotes for Leo’s live class notes.
To download the “data” directory at https://github.com/lcolladotor/jhustatcomputing/tree/main/data, you can do so manually 1 file at a time. But you can also:
Use the green “Code (downarrow)” button at https://github.com/lcolladotor/jhustatcomputing/tree/main to download the full course website. Either “git clone” via HTTPS (easier) or SSH (advanced), or download the full course zip file (easiest option but it is not linked via Git/GitHub; aka hard to update in the future).
Use
usethis::use_course()as documented at https://usethis.r-lib.org/reference/zip-utils.html.
To make it easier for you, I wrote the R code you can run inside your RStudio IDE project / Positron directory for your class notes. Your equivalent to https://github.com/lcolladotor/biostat776classnotes. See these lines of code for the details.
| Week | Lectures / due dates | Topics | Projects | |
|---|---|---|---|---|
| Module 1 | Statistical and computational tools for scientific and reproducible research | |||
| Week 1 | Lecture 1 | 👋 Course introduction [html] [Qmd] [R] | 🌴 Project 0 [html] [Qmd] [R] | |
| 👩💻 Introduction to R and RStudio [html] [Qmd] [R] | ||||
| Lecture 2 | 🐙 Introduction to git/GitHub [html] [Qmd] [R] | |||
| 💻 Reproducible Research [html] [Qmd] [R] | ||||
| 👓 Literate programming [html] [Qmd] [R] | ||||
| Module 2 | Data analysis in R | |||
| Week 2 | Lecture 3 | 🆒 Reference management [html] [Qmd] [R] | ||
| 👀 Reading and writing data [html] [Qmd] [R] | 🌴 Project 1 [html] [Qmd] [R] | |||
| Lecture 4 | ✂️ Managing data frames with Tidyverse [html] [Qmd] [R] | |||
| 😻 Tidy data and the Tidyverse [html] [Qmd] [R] | ||||
| Sept 7 | `🍂 Project 0 due | |||
| Module 3 | Data visualizations R | |||
| Week 3 | Lecture 5 | 🤝 Joining data in R: Basics [html] [Qmd] [R] | ||
| 📊 The ggplot2 plotting system: ggplot() [html] [Qmd] [R] | ||||
| Lecture 6 | 📊 The ggplot2 plotting system: ggplot() [html] [Qmd] [R] | 🌴 Project 2 [html] [Qmd] [R] | ||
| Sept 14 | 🍂 Project 1 due | |||
| Module 4 | Nuts and bolts of R | |||
| Week 4 | Lecture 7 | 🔩 R Nuts and Bolts [html] [Qmd] [R] | ||
| Lecture 8 | 🔩 Control structures in R [html] [Qmd] [R] | |||
| 🔩 Functions in R [html] [Qmd] [R] | ||||
| Week 5 | Lecture 9 | 🔩 Loop functions [html] [Qmd] [R] | ||
| Lecture 10 | 🐛 Debugging code in R [html] [Qmd] [R] | |||
| 🐛 Error handling code in R [html] [Qmd] [R] | ||||
| Sept 28 | 🍂 Project 2 due | |||
| Module 5 | Special data types in R | |||
| Week 6 | Lecture 11 | 📆 Working with dates and times [html] [Qmd] [R] | 🌴 Project 3 [html] [Qmd] [R] | |
| Lecture 12 | ✨ Regular expressions [html] [Qmd] [R] | |||
| Week 7 | Lecture 13 | 🐱 Working with factors [html] [Qmd] [R] | ||
| Lecture 14 | 📆 Working with text data and sentiment analysis [html] [Qmd] [R] | |||
| Module 6 | Best practices for working with data and other languages | |||
| Week 8 | Lecture 15 | ☁️ Best practices for data analyses [html] [Qmd] [R] | ||
| Lecture 16 | 🐍 Leveraging Python within R [html] [Qmd] [R] | |||
| Oct 19 | 🍂 Project 3 due | |||
| Historial lectures | Lectures used in previous years that you might want to browse out of curiosity. They cover aspects of R that are not as used as they used to be around ~2012. | |||
| 📊 Plotting systems in R [html] [Qmd] [R] | ||||
| 📊 The ggplot2 plotting system: qplot() [html] [Qmd] [R] |