This workshop will provide a gentle introduction to some of the commonly used quantitative data analysis techniques. We aim to show the participants that many techniques in quantitative methods are actually very intuitive, fun, easy to learn and implement. Once the participants get an intuitive understanding, they can start focusing on the interpretation of results and even design their own studies at a basic level; perhaps a survey. We will have a hands-on session showing the participants some of the core analysis techniques. We will mostly use the free and open-source software R. Below are some freely available resources for R. Many of these resources are online cookbooks and include hundreds of materials. Participants can copy/paste R codes for various analyses and start using the software right away. Feel free to explore and play around with these materials before coming to the workshop. We will also show application in STATA for those who might prefer different software.

Material/Readings
• R Examples Repository, Daniel Wollschlaeger: http://dwoll.de/rexrepos/index.html
• R for Data Science, Garrett Grolemund, Hadley Wickham: http://r4ds.had.co.nz/index.html
• A Language, not a Letter: Learning Statistics in R; An online collection of tutorials created by graduate students in psychology: http://ademos.people.uic.edu/index.html
• An Introduction to Statistical and Data Sciences via R, Chester Ismay and Albert Y. Kim:
http://moderndive.com/
• Learning statistics with R: A tutorial for psychology students and other beginners, Daniel Navarro: http://learningstatisticswithr.com/
• For those who might prefer a different software an excellent book STATA: A STATA Companion to Political Analysis by Pollock P.H. (2011)
• Additional material can be found on: http://www.statmethods.net/about/books.html
• Friendly statistics with lots of gentle introductions, YouTube channel of Joshua Starmer: https://www.youtube.com/user/joshstarmer