This material was developed by the DIME Analytics team as an introduction to R Statistical Package for its staff. It builds upon knowledge of Stata to explore features of R with impact evaluation applications in mind. It also assumes some degree of familiarity with DIME's coding practices. All sessions are designed to last 90 minutes.

01 - Introduction to R

• Introduction to RStudio, R syntax, objects and classes.

Formats:

• .html
• .pdf
• .Rmd

02 - Introduction to R programming

• Code organization, R libraries, loops, custom functions, and R programming practices.

Formats:

• .html
• .pdf
• .Rmd

03 - Data wrangling

• Basic functions for processing data using the tidyverse meta library.

Formats:

• .html
• .pdf
• .Rmd

04 - Data visualization

• An introduction to creating and export graphs in ggplot2.

Formats:

• .html
• .pdf
• .Rmd

05 - Descriptive analysis

• How to create and export descriptive statistics table in R.

Formats:

• .html
• .pdf
• .Rmd

06 - Geospatial data

• An overview of R resources on GIS.

Formats:

• .html
• .pdf
• .Rmd

This material is developed under MIT license. See http://adampritchard.mit-license.org/ or see the LICENSE file for details.

Luiza Cardoso de Andrade ([email protected]) - [email protected]

• Luiza Cardoso de Andrade
• Robert A. Marty
• Leonardo Teixeira Viotti
• Rony Rodriguez-Ramirez
• Luis Eduardo San Martin