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Introduction to Data Analysis Using Python
by
Fri, Sep 18, 2026
10 AM – 12 PM EDT (GMT-4)
Private Location (sign in to display)
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Registered
Details
Workshop format: Presentation (20%) and hands-on (80%)
Target audience: This workshop is ideal for those who are at the initial stages of doing independent research requiring quantitative analysis (term paper, dissertation, junior paper, senior thesis). Artificial intelligence models still require checking. How do you know what to check for if you do not know what to look for. This workshop will provide some fundamentals that will maximize your interaction and understanding when working with AI models.
Knowledge prerequisites: Some knowledge of Python would be beneficial.
Hardware/software prerequisites: Participants should install the Anaconda Python distribution (which includes Jupyter notebooks, NumPy, and pandas) on their laptops in advance. Instructions can be found in this guide. To use the AI assistant you will also need to install Positron.
Learning objectives: Participants will walk away with (1) a basic knowledge of how to prepare the data for working with pandas in a Jupyter notebook; (2) how to use pandas for data analysis with a basic understanding of descriptive statistics, data visualization, ANOVA, and regression; (3) the idea that data analysis is not just about running statistical models.
Speakers
Oscar Torres-Reyna
Manager of Statistical Services, Economics
Princeton University
Oscar Torres-Reyna is the manager of statistical services at the Economics department 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 degree in public administration, and an MPhil. and PhD in political science from Columbia University, all with a strong focus on data analysis.