BAN 6003: Intro to Programming with R
Welcome to Introduction to Programming with R! This course provides an intensive, hands-on introduction to the R programming language. You will learn the fundamental skills required to acquire, munge, transform, manipulate, and visualize data in a computing environment that fosters reproducibility.
Upon successfully completing this course, you will be able to:
- Perform your data analysis in a literate programming environment
- Import and manage structured and unstructured data
- Manipulate, transform, and summarize your data
- Join disparate data sources
- Methodically explore and visualize your data
- Develop your own functions
- And perform basic predictive analytic modeling
…all with R!
All required classroom material will be provided in class or online. Any recommended yet optional material will also be provided in the classroom notes.
||Lesson Description & Material
||Introduction & Reproducibility
||Intro to the course, R, and RStudio
||Managing workflow & reproducibility
||Exploratory Data Analysis
ggplot2 for visualization
dplyr for data transformation
||Preparing Your Data
||Importing & exporting data
tidyr for tidy data
||Controlling Your Data
||Factors & dates
||Advancing Your Skills
||Intro to statistical modeling
||Class project due
Course grades will consist of:
Final grades will be distributed according to the following cutoffs:
- A 94 – 100%
- A- 90 – 93%
- B+ 87 – 89%
- B 83 – 86%
- B- 80 – 82%
- C+ 77 – 79%
- C 73 – 76%
- C- 70 – 72%
- D & F Hopefully None!
We will use this software during the course. Plan on bringing a computer to each class meeting.
- R and RStudio will be used to perform all programming activities, assignments, and the final project. You can find details on how to download these here.
- Slack will replace e-mail and Blackboard for our course. You will receive an invitation to the WFU R slack team. You may wish to install one of the apps.
- Attendance: Your attendance is expected at every meeting. If you must be absent, I request that you notify me in advance of the class meeting.
- Academic Integrity: All students must adhere to the highest standards of academic integrity. Students are prohibited from engaging in plagiarism, cheating, misrepresentation, or any other act constituting a lack of academic integrity. Failure on the part of any individual to practice academic integrity is not condoned and will not be tolerated. Individuals who violate this policy are subject to adverse administrative action including disenrollment from school and disciplinary action.
- Grade appeals: If you think the grade of your work (homework, peer reviews, participation) is miscalculated, you have the right to appeal. The appeal must be done (through email) within 7 calendar days since the grade is released/posted. After that, your grade is final and will not be changed.
- Testing Policy: This is a project-based course. Consequently there will be no midterm or final exam.
- Late Assignments and Make-Ups: Late submissions will not be accepted.
- Tentative Plan: The course syllabus is a general plan for the course; deviations announced to the class by the instructor may be necessary.
I have drawn ideas or readings from the following syllabi: