Essential Fundamentals of R


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Course overview

Course type
Paid course
11 hours
46 lessons
Available on completion
Course author
Geoffrey Hubona, Ph.D.
  • Install R and RStudio and engage in a basic R session
  • Understand the characteristics of different data types and structures in R
  • Be able to read in data and write out data files from various sources
  • Sort, select, filter, subset, and manipulate tables of data in R
  • Create and execute their own user-defined functions in an R session
  • Understand how to use the apply() family of functions to execute various actions against different R data structures
  • Know how to use reshaping and recoding "short cuts" for changing data types and for rearranging data structures.


Data Types and Structures in R , Inputting & Outputting Data, Writing User-Defined Functions, and Manipulating Data Sets

Essential Fundamentals of R is an integrated program that draws from a variety of introductory topics and courses to provide participants with a solid base of knowledge with which to use R software for any intended purpose. No statistical knowledge, programming knowledge, or experience with R software is necessary. Essential Fundamentals of R (7 sessions) covers those important introductory topics basic to using R functions and data objects for any purpose: installing R and RStudio; interactive versus batch use of R; reading data and datasets into R; essentials of scripting; getting help in R; primitive data types; important data structures; using functions in R; writing user-defined functions; the 'apply' family of functions in R; data set manipulation: and subsetting, and row and column selection. Most sessions present "hands-on" material that demonstrate the execution of R 'scripts' (sets of commands) and utilize many extended examples of R functions, applications, and packages for a variety of common purposes. RStudio, a popular, open source Integrated Development Environment (IDE) for developing and using R applications, is also utilized in the program, supplemented with R-based direct scripts (e.g. 'command-line prompts') when necessary.

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