×

Introduction to R

January 10-12, 2024

Course Structure

The course will include six 3 hour sessions over 3 days.

WednesdayThursdayFriday
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

  1.  Understand the basics of R and RStudio, and be familiar with fundamental data structures such as vectors, data frames, lists, and classes. 
  2. Utilize simple statistical functions in R, such as calculating means and variances. 
  3. 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. 
  4. Apply advanced data wrangling techniques such as joins and pivots to merge and reshape datasets. 
  5. Create tidy data sets and generate visualizations using the powerful ggplot2 package. 
  6. Develop an understanding of loops and functions in R, along with the application of the map function from the tidyverse for efficient data processing. 
  7. 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

January 10-12, 2024

Course Structure

The course will include six 3 hour sessions over 3 days.

WednesdayThursdayFriday
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

  1.  Understand the basics of R and RStudio, and be familiar with fundamental data structures such as vectors, data frames, lists, and classes. 
  2. Utilize simple statistical functions in R, such as calculating means and variances. 
  3. 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. 
  4. Apply advanced data wrangling techniques such as joins and pivots to merge and reshape datasets. 
  5. Create tidy data sets and generate visualizations using the powerful ggplot2 package. 
  6. Develop an understanding of loops and functions in R, along with the application of the map function from the tidyverse for efficient data processing. 
  7. 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