This material was developed by the DIME Analytics team as an introduction to R Statistical Package for its staff.
R is a programming language for statistical analysis and data science. It is a powerful and flexible tool widely used among statisticians and data scientists, and has a growing user base in economics research. This course is designed to familiarize participants with the language, focusing on common tasks and analysis in development research, and showing how to use R through RStudio, a popular integrated development environment for R. The course will build upon comparisons to Stata syntax and requires familiarity with the use of do-files, loops and macros. It also assumes some degree of familiarity with DIME's coding practices. All sessions are designed to last 90 minutes.
- Introduction to the RStudio interface, R syntax, objects and classes.
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02 - Introduction to R programming
- Code organization, R libraries, loops, custom functions, and R programming practices.
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- Basic functions for processing data using the tidyverse meta library.
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- An introduction to creating and export graphs in
ggplot2.
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- How to create and export descriptive statistics table in R.
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- An overview of R resources on GIS.
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07 - Introduction to R Markdown
- An introduction to dynamic documents and R Markdown.
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This material is developed under MIT license. See http://adampritchard.mit-license.org/ or see the LICENSE file for details.
Luis Eduardo San Martin - dimeanalytics@worldbank.org
- Luiza Cardoso de Andrade
- Marc-Andrea Fiorina
- Robert A. Marty
- Maria Reyes Retana Torre
- Rony Rodriguez Ramirez
- Luis Eduardo San Martin
- Leonardo Teixeira Viotti
