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Data Science and AI Academy

Fundamentals of R and Posit (R Studio)

This is the pre-course to the one day workshop on April 6, 2024. Limited seating is available for this course.

This one-day intensive course is designed to introduce participants to R and RStudio (Posit), equipping them with the fundamental skills required to start their journey in data analysis and programming. The course begins with an overview of R and RStudio’s environment, highlighting how these tools are used for data manipulation, analysis, and visualization in various fields. Attendees will learn how to import, clean, and manipulate datasets using R’s dplyr package, along with how to create data visualizations using R’s ggplot2 package. Throughout, this course focuses on the principals of data transparency and reproducibility. By the end of the day, participants will have a solid foundation in R and RStudio, enabling them to confidently apply their new skills to real-world data analysis projects. This course is ideal for beginners with no prior experience in R or those looking to refresh their skills.

Prior to class

Requirements – A Laptop computer running any of Linux, Mac or Windows OS.

Date and Registration

  • Date: Saturday, March 30, 2024
  • Time: 8 a.m. to 5 p.m.
  • Location: Talley Student Union, Rm 4280
REGISTER TODAY

Instructors

John S. House, Ph.D., M.Stat

Staff Scientist, NIEHS | Adjunct Associate Professor, NC State 

StartEndProgram
8am8:30amArrival
8:30am9:30amR and Rstudio overview, navigation and setup
9:30am10amGetting data in and out of R
10am10:15amBREAK
10:15am11amWorking with vectors
11am12pmWorking with data frames
12pm12:45pmLUNCH
12:45pm1:45pmData munging with dplyr
1:45pm2:30pmMerging data in R with dplyr
2:30pm3pmData visualization I
3pm3:15PMBREAK
3:15pm4:15pmData visualization II
4:15pm5pmIntro to functional programming
This schedule is subject to change as the date approaches.

Concepts

  • Installing and loading packages
  • Opening and closing scripts
  • Help documentation access
  • The working directory and relative paths
  • Assignment operator and object browser
  • Rstudio Script Types – this course will focus on R markdown
    • .R vs .RMD and knitting to HTML output
  • Base R functions for delimited files
  • data.table package and fread()
  • Excel files from readxl package
  • Vector Creation and Types of Vectors (character, numerical, logical) using c()
  • Vector Operations (sum(), mean(), length(), min(), max())
  • Logical Operations
  • Indexing and Subsetting
  • Creation of data.frames()
  • Inspection with head(), tail(), dim(), str(), nrow(), ncol()
  • The $ notation
  • Adding columns and rows with rbind() and cbind()
  • Column calculations
  • Filtering Rows and Columns with filter() and select()
  • Creation of new variables with mutate()
  • Summarizing data with summarise()
  • Sorting and grouping operations with arrange() and group_by()

Left, right, full, inner joins

  • Base R graphics
  • Graphics in ggplot2
  • Parameters
  • Default values
  • Loops