Introduction to R
Course Level: Foundation (6 hours)
In this course, you’ll explore the versatility of R, a powerful language for statistical computing and graphics. Discover the benefits of using R and get started with the basics. Gain confidence with the user-friendly RStudio interface and learn fundamental R concepts. You’ll also dive into the Tidyverse, a collection of packages for data storage, visualization, and manipulation. This course offers a solid foundation to kickstart your journey with R!
Book: Introduction to R
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Course Details
Outline
- Introduction to R:
- Overview
- Background
- Features of the R statistical programming system
- Data entry:
- Importing data
- Data types:
- Numeric
- Float
- Binary
- R environment:
- Introduction
- Working directory
- Creating/using scripts
- Saving data and results.
- R graphics:
- Brief introduction to {ggplot2}
- Creating, editing and storing graphics
- Summary statistics:
- Measures of location and spread
- Manipulating data in R:
- Describing how data can be manipulated using logical operators and {dplyr}
- Vector operations:
- Details of R’s vectors operations
Learning outcomes
Session 1
By the end of session 1, participants will…
- have a clear understanding of R/RStudio IDE and its background.
- be familiar with navigating the RStudio IDE.
- understand the core fundamentals of R.
- understand functions and arguments.
- be able to create vectors and applying functions.
- be exposed to the tibbles and {tidyverse} package.
Session 2
By the end of session 2, participants will…
- be able to comfortably import, export, and store data in R.
- have a basic introduction to graphics with {ggplot2}.
- have a basic understanding of manipulating data manipulation with {dplyr}.
- understand logical and relational data partitioning.
This course does not include:
- An advance usage of {ggplot2}.
- Advanced data analyses, wrangling and manipulation techniques. For data cleaning and manipulation see our Data Wrangling with Tidyverse course.
- A description of automated reporting using R Markdown, see our course Reporting with R Markdown.
Prior knowledge
No prior programming knowledge of any kind is assumed. This course is suitable for all fields of work. Previous attendees include biologists, statisticians, accountants, engineers & students, i.e., anyone who uses a spreadsheet!
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