Stata vs. R: Making The Move

With the expanding use of R as a main data analysis tool (sorry Python) and the many publications utilizing this language, the relationship to other tools is a hot topic of discussion amongst the analytic and economic community. R provides a flexible environment for data wrangling, mining and analysis.

Resulting from all the chit-chat, STATA users are wondering what R is and how its functionality relates to the language and packages they already know. There are similarities in the approach between the languages - such as open command, ability to write new procedures and the in-memory approach. Both programs also have strong support communities developing new modules to increase functionality. However, a significant difference is that R it is open source. As such anyone has full access to the functionality, versus the expensive proprietary software of STATA.

Few specific aspects of data wrangling and analysis will be covered in this talk.Both STATA code and R code will be presented to demonstrate parallel approaches between the two codes.

We will aim to open the way for STATA users to understand the use of R and how it can improve future analytical requirements. Come join us to see a real-time side-by-side data wrangling using STATA and R.

Our Teachers

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Refael Lav (Rafi)

Rafi is an EY data consultant with the Enterprise Intelligence - Data analytics practice. Rafi is a practitioner with a background in economic research, finance and data analytics including algorithms, data management, business intelligence, statistical analysis, outlier detections, and data mining. He has consulted on new product developments, business initiatives, process reengineering, technology solutions and efficacy implementations. He has developed R models for EY as well as the EY R training. Rafi holds a Master's of Science of Finance Johns Hopkins University and B.S. Economics from George Washington University. Follow Rafi on Twitter at @refaellav

Jason Burwen

Jason is formerly a consultant with FSC Group (now Nexant), where he worked with large smart meter data extracts in STATA to craft experimental research designs and conduct data analysis on demand-side issues in electricity--i.e., how electric rates and other utility programs affect residential, commercial and industrial energy consumption patterns. He came to this from being a grad student working with sensor, survey, and other data from improved biomass cookstoves in developing countries. Jason's training is in econometrics and experimental & quasi-experimental research design. He currently works in energy policy at the Bipartisan Policy Center. Follow Jason on Twitter at @jburwen