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 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.