Course Instructor

Alex Edwards

Office Hours: Tuesdays 11:30am - 3pm, Open Zoom Link to be Posted

Course Teaching Assistants

Lindsey Schader
- 3rd Year PhD - - Office Hours: TBD

Nanxi Guo
- 2nd Year MSPH - - Office Hours:TBD

Lydia Rautman
- 2nd Year MPH - - Office Hours: Slack TBD

Course Meetings

Wednesday 3:15 - 5:05 on Zoom (Link to be Posted)

Grade Scale

Grade Range
A [95 - 100)
A- [90 - 95)
B+ [85 - 90)
B [80 - 85)
B- [75 - 80)
C [65 - 75)
F < 65

Introduction

This class is designed to provide an introduction to R and R programming. The objectives of this course are for the student to be able to accomplish the following: Understand the concepts of the R programming language

  • Write and debug R functions
    • Create useful graphs
    • Reshape and aggregate data
    • Create Reproducible R Code for distribution and collaboration

This class is for students whose research requires non-trivial amounts of data manipulation and analysis. As with other domains such as Biology and Genetics, Public Health is experiencing a “Data Deluge” which is being addressed in large part by the application of innovative quantitative approaches that require a knowledge of R programming to implement. Therefore, we concentrate on developing programming skills as opposed to data analysis and/or statistical techniques although we do use examples from both these areas to illustrate important concepts. While this is an introductory class, any previous programming experience with other languages will be helpful. This class takes place in the Fall Semester 2020. The schedule below represents the intended content although the instructor may elect to substitute in topics as deemed appropriate.

MPH/MSPH Foundational Compentencies

  1. Analyze quantitative and qualitative data using biostatistics, informatics, computer-based programming and software, as appropriate
  2. Perform effectively on interprofessional teams
  3. Apply systems thinking tools to a public health issue

Seeking Help

Computer programming can be frustrating because computers are stupid, and error messages are not always helpful. Fortunately, help is out there.

Outside of class time, I can provide help in office hours and (sparingly) by email, but try to refrain from reaching out until you have exhausted other sources of help such as StackOverflow or RStudio Community.

Why? Because finding solutions using documentation and online resources is an essential skill for learning any programming language. You will learn these tools (especially R) better by learning to help yourself!

Note that the course material is designed to be self-contained enough that everything you need to complete take-home assignments should be included in course notes, and the resources provided as we go.

Obviously, problems that are specific to your individual project needs may require solutions from beyond the course material.

Textbooks

None Required; however, a huge list will be posted for you to use as resources. Most are free on the web. I may post some items that I feel you may find useful via Canvas.

Assignments and Weights

Assignments Weight
Homeworks (Five) 15%
Peer Review Homework Process (Five) 15%
Pick Your Data Set 10%
Examine Your Data Set 10%
Analyze Your Data Set 25%
Present Your Findings Side Deck 25%
Total: 100%

Please Note: Each student in my courses is allotted 5 total extension days that may be used on any assignment. You may use single days or up to two days per assignment. You must notify me via email before the assignment is due that you wish to use extension days.

Course Schedule

Dates Activity
8/19 Course Introduction and Motivation, RStudio
8/26 History of R, Significance of Wickam, R Basics
9/2 Project Based Workflow, R Markdown, Github
9/9 R Data Structures and Tidy Data
9/16 Dude? Where’s my Data?
9/23 Manipulation of Data
9/30 Data Visualization Part One
10/7 Summarizing Data
10/14 Shaping Data: How R Will Frustrate You
10/21 What They Don’t Teach You In School About Real Data
10/28 Real Data, Real Messy Part One
11/4 Data Visualization Part Two
11/11 Text Analysis
11/18 R as a GIS
11/25 Classes End
12/2 Project Work
12/9 Project Due

RSPH POLICIES

Accessibility and Accommodations

Accessibility Services works with students who have disabilities to provide reasonable accommodations. In order to receive consideration for reasonable accommodations, you must contact the Office of Accessibility Services (OAS). It is the responsibility of the student to register with OAS. Please note that accommodations are not retroactive and that disability accommodations are not provided until an accommodation letter has been processed.

Students who registered with OAS and have a letter outlining their academic accommodations are strongly encouraged to coordinate a meeting time with me to discuss a protocol to implement the accommodations as needed throughout the semester. This meeting should occur as early in the semester as possible.

Contact Accessibility Services for more information at (404) 727-9877 or . Additional information is available at the OAS website at http://equityandinclusion.emory.edu/access/students/index.html

Honor Code

You are bound by Emory University’s Student Honor and Conduct Code. RSPH requires that all material submitted by a student fulfilling his or her academic course of study must be the original work of the student. Violations of academic honor include any action by a student indicating dishonesty or a lack of integrity in academic ethics. Academic dishonesty refers to cheating, plagiarizing, assisting other students without authorization, lying, tampering, or stealing in performing any academic work, and will not be tolerated under any circumstances.

The RSPH Honor Code states: “Plagiarism is the act of presenting as one’s own work the expression, words, or ideas of another person whether published or unpublished (including the work of another student). A writer’s work should be regarded as his/her own property.” (http://www.sph.emory.edu/cms/current_students/enrollment_services/honor_code.html)