Introduction to Data Analysis using Python

Name: Introduction to Data Analysis using Python
Start: 2024-02-21T10:00:00-05:00
End: 2024-02-21T12:00:00-05:00
Location: Private Location (sign in to display)

by PICSciE/Research Computing

Training/Workshop Programming Languages Research & Data Analysis Undergraduate Research

Wed, Feb 21, 2024

10 AM – 12 PM EST (GMT-5)

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Details

This workshop will get students started in data analysis using the pandas Python package. It will briefly cover different components of data analysis and connect them with the goal of extracting meaning from data. We will go over an example to illustrate the data analysis process from beginning to end.

Workshop format: Presentation and hands-on

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).

Knowledge prerequisites: None

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 here: https://bit.ly/3c7IXez

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.

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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.

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Co-hosted with: GradFUTURES, The Graduate School

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