Introduction to R
January 10-12, 2024
Course Structure
The course will include six 3 hour sessions over 3 days.
| Wednesday | Thursday | Friday |
|---|---|---|
| Session 1 (9-12) | Session 3 (9-12) | Session 5 (9-12) |
| Session 2 (1:30-4:30) | Session 4 (1:30-4:30) | Session 6 (1:30-4:30) |
Course Instrcutor: 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: $100 LUC students; $200 non-LUC students, faculty, and staff
Course Structure
The course will include six 3 hour sessions over 3 days.
| Wednesday | Thursday | Friday |
|---|---|---|
| Session 1 (9-12) | Session 3 (9-12) | Session 5 (9-12) |
| Session 2 (1:30-4:30) | Session 4 (1:30-4:30) | Session 6 (1:30-4:30) |
Course Instrcutor: 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.