R is an Open Source software package (free to use!) that is used widely to analyze data, among other things.
I. Get the Software We suggest that you install R and then R Studio as outlined below
- Install R: Go to http://www.r-project.org and install the latest version of R (install base)
- Install RStudio: Go to http://www.rstudio.com and install the front-end RStudio
See “Intro to R” in the next section “JMU R Videos” to see how to install the software. The programming language is R, and RStudio is the interface that you will use to run R code.
II. On Github R Programming: Zero to Pro
III. JMU R Videos Watch these R Tutorials created by Andre Neveu at JMU
- Intro to R (includes video demonstration of downloading and installing R and RStudio)
- Using R – Basic Calculations, Vectors, and Matrices
- Importing Data in R
- Plotting in R
- Statistics in R
- Simple Regression in R
IV. LinkedIn R Video Training (You have free access to LinkedIn learning using your JMU eID)
- Learning R (approx 3 hours of video content) Covers installing R, RStudio and many basics
- Data Wrangling in R (approx 4 hours of video content) Covers the basics of tidyverse.
- Data Visualization in R with ggplot2 (approx 2 hours of video content) Visualizing data using ggplot2 in R/RStudio
- R Essential Training: Wrangling and Visualizing Data (approx 4 hours ) More graphing and visualization in R/RStudio
- R Essential Training Part 2: Modeling Data (approx 4 hours) Data analysis including statistics and regression in R/Rstudio
V. Coursera Courses: On-line Courses for Learning
FYI: Coursera courses provide free on-line learning. When you enroll, you will be prompted to signup for a certificate that involve a fee. However, all of the courses allow you to AUDIT the course for free. This free option is sometimes difficult to find because it appears in small print. Look carefully, it is typically at the bottom left of the pop-up box when you click on Enroll. The free AUDIT option will give you access to all the course materials except for some quizzes and projects:
- Getting Started with Data Visualization in R from Johns Hopkins University
- Data Visualization in R with ggplot2 from Johns Hopkins University (same name as the LinkedIn course but not a duplicate!)
- R: Want to get prepared to take Econometrics Econ 385? Try Coursera’s Linear Regression and Modeling. It is taught with R. Not as in depth as JMU’s Econ 385 course but good preparation.
- R: Want to improve your statistics knowledge? the stuff that comes before econometrics? Check out Coursera’s Inferential Statistics
VI. Additional Resources on R/RStudio
- Data Visualization: A Practice Introduction (Kieran Healy) free on-line book about using R to visualize data
- A handy manual by Eric Nord at Penn state is Essential R: What you need to get started.
- The Pirates Guide to R
- Applied Econometrics with R comprehensive resources for doing econometrics in R
- YouTube Play List for Introduction to R for Economists: covers the basics of data sets, summary statistics and graphs, bivariate and multiple regression, times series, and panel data.
- Introduction to Econometrics with R from SciencesPo Department of economics
- Regression in R from Princeton
- Panel Data in R from Princeton
- Creating new variables in R using an existing data frame from Quick-R
- Nice Regression Output (stargazer) from R for non-Latex users from Princeton
- More on Stargazer
- A comprehensive list from CRAN Task View of R Packages for Econometrics, Finance and Time-Series – lots of overlap
- From Penn State: Topics in R Statistical Language course.
- A ModernDive into R and the Tidyverse
- Line plots using ggplot2()
- Scatterplots using ggplot2()