R Programming Training Courses: Data Preparation for Analysis and Data Analysis
These training courses are an introduction to the program language R with the purpose of getting familiar with the commands in such a way that participants will feel self-prepared to continue on their own. The content covers data wrangling and basic statistical analysis at the graduate level. Therefore, it is required that participants have taken at least one statistics course at the graduate level. See Syllabus for more information. The training courses are Data Preparation for Analysis and Data Analysis. Both courses will be offered during the spring semester, and you will have 16 weeks to complete one or both courses.
Content Summary
- Data Preparation for Analysis:
- Introduction to basic commands
- Data preparation
- Data cleaning
- Exploratory data analysis
- Data Analysis (parametric and non-parametric):
- Inference about the mean and the median
- One-way/ two-way ANOVA and correlation
- Linear and multilinear regression
- Inference about categorical variables
- Logistic regression
You can take either course, but it is strongly recommended to take Data Preparation for Analysis before taking Data Analysis.
Syllabus
Training Schedule for Spring 2026
- R Data Preparation for Analysis: January 12 - February 6
- R Data Analysis: February 9 - March 13
- Participants who do not finish by the end date may extend either course until April 24.
Registration
The registration period is now open and will close on 01/09/2026 at 5:00 PM.
Time Commitment
The training series is self-paced. It is recommended to complete at least a module per week.
Need different dates? For consultation or to schedule an event, request training.
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