R

Table of Contents

R is a functional programming language used for statistical computing and graphics. Learn how to use R in our beginner's tutorial guide.


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Introduction
Vectors

  1. Introduction
  2. A beginner's guide to the R statistical programming language.

    1. What is R and setup
    2. Learn how to use and install R and its IDE RStudio for your statistical analyses in our beginner's tutorial series.


    3. Variables and Commands
    4. Learn about basic commands and variables in R, including how to remove variables from your environment. Also we'll look into RStudio and the basics of how to operate each panel.


    5. Functions
    6. Learn how to define your own functions, which are crucial to simplifying your R analysis workflow. Also find out what formal parameters and actual arguments are, and how to declare default values as arguments in your function.


    7. Help
    8. Need help or an example of how a command is used in R? No fear! R comes equipped with several functions that allows you to find help, straight from the console.


    9. Scripts
    10. Learn how to load and run an R script directly from the command line, using the RScript command or R CMD BATCH. Also, learn the differences between the aforementioned two ways.


    11. Startup
    12. Learn how to create and edit the R configuration file, which enables you to select an editor and set your current working directory.


    13. Datasets
    14. Learn how to save all your objects within your work session to an R dataset, either automatically or manually.



  3. Vectors
  4. Learn about the core data structure in R, vectors.

    1. Introduction to Vectors
    2. Learn how to declare vectors, check their types, access vectors by index, and name each element within a vector.


    3. Sequences and Repetitions in R
    4. Learn how to use the seq() and rep() functions in R to create vectors.


    5. Recycling and Vector Arithmetic
    6. Learn how to perform vector arithmetic, and learn what it means to recycle a vector in R.


    7. Filtering Vectors
    8. Learn how to filter vectors in R using the all(), any(), which(), and subset() functions.