An introduction to R and RStudio

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Outline

  • The following topics will be covered in this lecture:

    • What is R and RStudio
    • How do we write code?
    • How to install packages
    • How to get help in R

Introduction

  • This course will lean heavily on programming;

    • while it is possible to perform statistical analyses by hand for some very simple “toy” problems, realistic problem solving must be done on a computer.

  • This course does not assume that you are already familiar with programming;

    • this course will also not require a deep knowledge of programming or computer science.
    • However, everyone is responsible to learn enough R to become proficient with standard modeling and plotting functions.

  • Students are recommended to use the lessons in Sofware Carpentry as a free reference for scientific programming in R.

What is R?

  • There are a number of common choices of programming/ scripting languages for performing statistical modelling, e.g.:
    • SAS
    • SPSS
    • STATA
    • Python
    • R
  • We will use R for the following reasons:
    1. it is free and open source software with extensive documentation and tutorials available;
    2. it has well established libraries for statistical modeling with a wide functionality;
    3. the entry barrier to using the R language in terms of computer science training is very low; and
    4. there are free interactive, introductory lessons from DataCamp which will be used for homework assignments for additional practice outside of class.

Required software sources

RStudio