Data Analysis and Visualization for Beginners: R, Python and Stata

The Data Analysis and Visualization for Beginners workshops are hands-on and meant to introduce students to the use of R, Python, and Stata for data analysis. These workshops are intended for beginners, for those who do not have any experience with the use of statistical software, and/or for those who need a refresher. This intensive session provides the unique opportunity to see how the same type of analysis is done across different environments. We will focus on importing data, cleaning, preparing, and merging. We will go over some basics of data visualization, quantitative methods (descriptive statistics, mean comparison, linear regression), and text analysis (for R and Python: word frequencies, wordclouds, and sentiment analysis). This would be an encore from the sessions taught in Wintersession 2021.

Learning objectives:

1) Remove the fear of using statistical software for data analysis.
2) Get started on using statistical software.
3) Have a basic understanding on how the software works.
4) Perform same analysis using different environments.
5) Understand the basic components of the "Anatomy of Data Analysis".

Knowledge prerequisites:

No previous knowledge of statistics and/or statistical software required.

Hardware/software prerequisites:

The session is meant to be hands-on. It is highly recommended to have the Python, Stata, and/or R/RStudio installed and running properly in your computer. Here are some instructions:

For R/RStudio

A detailed set of instructions for installing both R and RStudio can be found on this page:
 
https://www.princeton.edu/~otorres/InstallingRStudio.pdf  
 
For a basic tutorial for RStudio see here:
 
https://dss.princeton.edu/training/RStudio101.pdf  
 
For an extensive set of tutorials on R/RStudio basics, here:
 
https://dss.princeton.edu/training/

For Python

We will run Python code using Jupyter Notebook, a web-based application that runs in your browser. The easiest way to install Python and Jupyter Notebook is by installing the ‘Anaconda Suite’, go to the link below and download the 64-bit version available for your operating system:   

https://www.anaconda.com/products/individual

If needed, some additional installation instructions here:  
 
https://docs.anaconda.com/anaconda/install/

For Stata

If it is installed on your machine, make sure that it is working properly. To give you an overall idea of Stata see here

https://dss.princeton.edu/training/StataTutorial.pdf  

If you do not have a Stata license, you can use the virtual version provided by the University via Princeton Virtual Desktops (PVD), see instructions in this tutorial:

https://dss.princeton.edu/training/StataPVD.pdf

If you are having trouble login into PVD or setting up your OneDrive, please contact OIT at helpdesk@princeton.edu.

Session format:

Virtual via Zoom, demo, and hands-on/collaborative.

What to expect:

Intensive workshop (meets on a single day from 10am - 5pm EST, 7 total hours of meeting time). Attendees will have the opportunity to do the same type of analysis using Python, R, and Stata. We will start with R/RStudio, then we will break for lunch from 12 pm to 1 pm. We will continue with Python and then Stata. We will try to have roughly about two hours per software but this might change depending on how the session goes.

Meet the facilitator:

Oscar Torres-Reyna is a data and statistics consultant at Princeton University. Oscar assists students working on their independent research projects that require data analysis and/or visualizations (junior papers, senior thesis, dissertations, term papers). He has taught introductory data analysis workshops at Princeton since 2009 and he is currently a part-time lecturer in Data Analytics at the Economics department at Rutgers University-New Brunswick. When Oscar first came to Princeton in 2007, he brought with him about twenty years of work/research experience in public, private, and academic sectors. He has a BA in economics from the School of Economics/UNAM (Mexico) and a diploma in applied statistics from ITAM (Mexico). He also holds a masters in public administration, and an MPhil. and PhD in political science from Columbia University, all with a strong focus on data analysis.


To request accommodations for this event, please contact the workshop or event facilitator at least 3 working days prior to the event.

 

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