Skip to content

Commit

Permalink
Update README.md
Browse files Browse the repository at this point in the history
  • Loading branch information
luizaandrade authored Dec 22, 2018
1 parent 895e3c2 commit daa23f5
Showing 1 changed file with 6 additions and 7 deletions.
13 changes: 6 additions & 7 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -4,16 +4,15 @@
This material was developed by the [DIME Analytics](https://worldbank.github.io/dimeanalytics/) 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](https://dimewiki.worldbank.org/wiki/Stata_Coding_Practices).

## Version
The master branch version was adopted in DIME's [Field Coordinator Training](http://www.worldbank.org/en/events/2018/04/09/manage-successful-impact-evaluations) in June 18.
The master branch version was adopted in DIME's R Couse in November/December 2018.

## Content
It currently includes the following content:
1. Intro to R: introduction to RStudio, R syntax, objects and classes. Designed for a 3h session.
1. Coding Best Practices in R: uses and R master script to explore code organization, loops, custom functions and if statements. Designed for a 1h30 session.
1. Data Processing: basic functions for porcessing data. Designed for a 2h session.
1. Descriptive Statistics: how to create and export descriptive statistics table in R. Designed for a 1h30 session.
1. Data Visualization: an introduction to creating and export graphs in ggplot2. Designed for a 1h30 session.
1. Geopatial Data: an overview of R resources on GIS. Desined for a 3h session.
1. Intro to R: introduction to RStudio, R syntax, objects and classes.
1. Descriptive Analysis: how to create and export descriptive statistics and regression tables in R.
1. Data Visualization: an introduction to creating and export graphs in ggplot2.
1. Spatial Data: an overview of R resources on spatial data and maps creation using ggmap.
1. Data Processing: basic functions for processing data (subsetting, merging, appending).

## License
This material is developed under MIT license. See http://adampritchard.mit-license.org/ or see [the `LICENSE` file](https://github.com/worldbank/ietoolkit/blob/master/LICENSE) for details.
Expand Down

0 comments on commit daa23f5

Please sign in to comment.