#Instructors Guide for GPS Intro to R
Time/Date: noon-1:30, M/W (unless noted) Room: ??
We will use gh-pages to publish the syllabus and assignments/code.
Course github: tbd
We'll use RStudio to teach and live code. Read and work through the lessons below and then use as scripts for the classes you teach. After class, put up your live code script into the github repo. We won't provide the links to these lessons to the students until after each class. Because the lessons provide solutions and challeges we will use in the course, we probably will want to create adapted verisons in our repo.
Lessons will come from Software Carpentry Lesson R for Reproducible Scientific Analysis http://swcarpentry.github.io/r-novice-gapminder/.
GitHub source for R Course: https://github.com/swcarpentry/r-novice-gapminder
Instructors guide: http://swcarpentry.github.io/r-novice-gapminder/instructors.html
- Jan.4 - Setup & Intro (Tim)
- Intro to course - syllabus - weekly assignments (15m)
- Intro to R , RStudio & getting help (30 min)
- Note: This will be v. up pace
- Data structures in R 1: vectors, matricies, factors, lists(45m)
- Supplemental lesson - R project Management (30 min)
- Jan. 6 - Data structures/subsetting (Hyeonsu)
- Jan. 11 - Functions (Tim)
- Creating functions - (45m)
- Plotting with GGPLOT2 1 (45m)
- Jan. 13 - Plotting, control flow & writing data (Hyeonsu)
- Plotting with GGPLOT2 2 (25m) - we need to break off point from GGPLOT 1, if I cover all of 1 you can add supplemental lesson.
- Vectorization (30m)
- Control flow (35m)
- Supplemental lesson - Writing data (20m)
- Jan. 18 - Data preparation & cleaning (tim)
- Data frame manipulation: Dplyr (90m)
- Split-apply-combine: plyr (60m)
- Note: I will combine these two
- Jan. 20 - Data cleaning (Hyeonsu)
- Data frame manipulation: Tidyr (60m)
- Wrap-up (15m)