R Bootcamp Day 1: Introduction to R, RStudio, and Quarto Markdown

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R Bootcamp Day 1: Introduction to R, RStudio, and Quarto Markdown

Event Details

Date:
Time: to
Mode: Zoom
Location: Online, Online - synchronous
Instructor: Alexis Cenname

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This is part 1 of a four-part R Bootcamp  (June 11 to 14, 2024).

Description: Participate in our very first R Bootcamp Week for a deep dive into R programming. The bootcamp unfolds through a series of focused sessions that cover the entire data analysis process, from importing and cleaning data to sophisticated data manipulation and visualization techniques using the tidyverse package. Each workshop builds on the last, ensuring a comprehensive understanding and practical application of R for data analysis.

Day 1: In "Introduction to R, RStudio, and Quarto Markdown," you'll familiarize yourself with the RStudio interface and learn to create integrated Quarto Markdown documents.

Target Audience: The target audience for this workshop series is beginners and intermediates in data science, particularly those interested in learning R programming for data importation, exploration, cleaning, and visualization.

Prerequisites: None 

Overall learning objectives for the series: 

By the end of this workshop series, learners should be able to: 

  • Use the RStudio Server to create Quarto Markdown documents that combine R code with output and text 

  • Use R to import and examine data 

  • Produce numerical and graphical summaries of a data set and its variables 

  • Perform basic data cleaning and management with R 

Day 1: Introduction to R, RStudio, and Quarto Markdown 

  • Navigate the R/RStudio interface 

  • Describe basic components of R code 

  • Describe the basic functionality of Quarto Markdown 

  • Use RStudio to create a new Quarto Markdown document 

Day 2: Data Centric R with tidyverse 

  • Describe various data types in R 

  • Use functions to examine a data set 

  • Import data sets from various sources 

  • Export data to flat files 

Day 3: Data Exploration in R with tidyverse 

  • Use functions to create numerical summaries of data 

  • Describe the “grammar” of graphics in ggplot2 

  • Create visualizations of data of various types 

Day 4: Data Wrangling in R with tidyverse 

  • Filter and subset data by rows or columns 

  • Create new variables 

  • Transform data from long to wide and from wide to long 

  • Identify and appropriately handle missing values 

  • Merge data sets 

Each workshop builds on the last, ensuring a comprehensive understanding and practical application of R for data analysis. 

 

Upon completing this class, you should be able to:
  • Navigate the R/RStudio interface
  • Describe basic components of R code
  • Describe the basic functionality of Quarto Markdown
  • Use RStudio to create a new Quarto Markdown document
Level
Novice
Recording status
This class will be recorded and shared with attendees.
Class Materials
Class materials will be shared with attendees.
See more learning options on this topic: R Programming