Introduction to R
January 8-10, 2025
Course Structure
The course will include six 3 hour sessions over 3 days.
| Wednesday | Thursday | Friday |
|---|---|---|
| Session 1 (9a-12p) | Session 3 (9a-12p) | Session 5 (9a-12p) |
| Session 2 (1:30p-4:30p) | Session 4 (1:30p-4:30p) | Session 6 (1:30p-4:30p) |
Course Instructor: Matt Stuart
Location: Cuneo Hall 318
Learning Objectives
- Understand the basics of R and RStudio, and be familiar with fundamental data structures such as vectors, data frames, lists, and classes.
- Utilize simple statistical functions in R, such as calculating means and variances.
- Perform data wrangling tasks effectively, including reading and writing various file formats (e.g., CSV, XLSX) and utilizing Tidyverse functions like select, filter, and mutate for data manipulation.
- Apply advanced data wrangling techniques such as joins and pivots to merge and reshape datasets.
- Create tidy data sets and generate visualizations using the powerful ggplot2 package.
- Develop an understanding of loops and functions in R, along with the application of the map function from the tidyverse for efficient data processing.
- Demonstrate the skills acquired throughout the course by creating a comprehensive data "dive" report, showcasing your ability to analyze and present data effectively.
Registration Information
Cost for participation: $150 LUC students; $300 non-LUC students, faculty, and staff
Course Structure
The course will include six 3 hour sessions over 3 days.
| Wednesday | Thursday | Friday |
|---|---|---|
| Session 1 (9a-12p) | Session 3 (9a-12p) | Session 5 (9a-12p) |
| Session 2 (1:30p-4:30p) | Session 4 (1:30p-4:30p) | Session 6 (1:30p-4:30p) |
Course Instructor: Matt Stuart
Location: Cuneo Hall 318
Learning Objectives
- Understand the basics of R and RStudio, and be familiar with fundamental data structures such as vectors, data frames, lists, and classes.
- Utilize simple statistical functions in R, such as calculating means and variances.
- Perform data wrangling tasks effectively, including reading and writing various file formats (e.g., CSV, XLSX) and utilizing Tidyverse functions like select, filter, and mutate for data manipulation.
- Apply advanced data wrangling techniques such as joins and pivots to merge and reshape datasets.
- Create tidy data sets and generate visualizations using the powerful ggplot2 package.
- Develop an understanding of loops and functions in R, along with the application of the map function from the tidyverse for efficient data processing.
- Demonstrate the skills acquired throughout the course by creating a comprehensive data "dive" report, showcasing your ability to analyze and present data effectively.