Introduction to Coding in R: Data Science and Simulation for Public Health and the Life Sciences

Course Logistics

1. Course location: 207 Russell Hall
2. Syllabus
3. EPID 7500 R DataCamp Course (you must sign-up via email invite)
4. External R Resources
   1. Hadley Wickham’s Online R Book
   2. David Romney’s list of online R resources
   3. Use R! Book Series (free UGA online access) has many options, most relevant being Beginner’s Guide to R by Zuur
   4. Mixed Effects Models and Extensions in Ecology by Zuur (free UGA online access)
   5. Johns Hopkins Coursera Course on R
5. Submit anonymous feedback to Steve at any time
6. RStudio Cheatsheet
7. List of commonly used functions (CSV file, right click to download)
8. Final Project Instructions (updated 11/13)
   1. Final Project Alternative from Nov 9 assignment forward: EPG & HB code

	Date (all times are 2-4:30pm)	Topic	Assignments Due	In-Course Slides/Excercises
1	Aug 14	Course Introduction	Pre-course survey, Rescheduling Preference, Rescheduling Doodle Poll	1. Download RStudio 2. Download R 3. Live Coding Day 1 (DHS plotting exercise)
2	Aug 22 (Tues)	Tidyverse I	Introduction to R, Working with the RStudio IDE Part 1, Importing Data Into R	1. Intro to RStudio Slides 2. Basic R Slides 3. Data Input & Output Slides 4. Live Coding Day 2 (packages, data input/output, if/else, pattern finding) 5. Recorded lectures posted on ELC
3	Aug 28 (ending at 4pm)	Tidyverse II	Cleaning Data in R, Reporting with R Markdown	1. Live Code (updated as Steve saves it) 2. Complete version of in class excercises
4	Sep 14 (Thurs)	Tidyverse III	Data Manipulation in R with dplyr	1. Course Pace Feedback Survey #1 2. Live Code (updated as Steve saves it)
5	Sep 18	Data Visualization	Data Visualization with ggplot2 (Part 1)	1. Binomial simulation in R 2. Simulating smoking & lung cancer data
6	Sep 25	Algorithmic Thinking I	Intermediate R	1. Simulating smoking & lung cancer data II: Prevalence ratios, functions, and non-parametric resampling inference 2. Live updated version of above code
7	Oct 2	Power calculations; Introduction of Final Project	Writing Functions in R	1. Course Pace Feedback Survey #2 2. Code for today 3. Live updated version of above code
8	Oct 9	Simulating random normal samples and confidence intervals: Part I	Data Visualization with ggplot2 (Part 2)	1. Confidence Intervals 2. Live edited version of above code 3. Complete version of the above code
9	Oct 12 (Thurs)	Simulating random normal samples and confidence intervals: Part II	Data Visualization with ggplot2 (Part 3): Only Chapters 1 and 3	See links to code from Oct 9 (we edited the live edited version in class such that it's now similar to the complete code)
10	Oct 16	Simulating the linear model I	Intermediate R (Practice)	1. Linear model I
11	Oct 23	Simulating the linear model II	Work on project.	1. Linear Model II
12	Nov 2 (Thurs)	Simulating the logistic regression model.	Work on project.	1. Logistic Regression I
13	Nov 6	Simulating the logistic regression model.	Work on project.	1. Logistic Regression II
14	Nov 9 (Thurs)	TBD	Work on project.	1. Confounding I
15	Nov 13	TBD	Work on project.	1. Confounding II