Online Stata Three-Part Short Course: Part 1

This is an online 3-part short course (held over three afternoons – October 6, 7 and 8, 2020). Stata Part 1 will offer an introduction to Stata basics. Part 2 will teach entering data in Stata, working with Stata do files, and will show how to append, sort and merge data sets. Part 3 will... Read more »

Online Stata Three-Part Short Course: Part 2

This is an online 3-part short course (held over three afternoons – October 6, 7 and 8, 2020). Stata Part 1 will offer an introduction to Stata basics. Part 2 will teach entering data in Stata, working with Stata do files, and will show how to append, sort and merge data sets. Part 3 will... Read more »

Online Stata Three-Part Short Course: Part 3

This is an online 3-part short course (held over three afternoons – October 6, 7 and 8, 2020). Stata Part 1 will offer an introduction to Stata basics. Part 2 will teach entering data in Stata, working with Stata do files, and will show how to append, sort and merge data sets. Part 3 will... Read more »

Event Series Text Analysis Using R

Text Analysis Using R

Text Analysis Using R This two-day workshop hosted by the Odum Institute for Research in Social Science will introduce participants to the basics of text analysis in R. Text analysis is a promising new approach that uses machine learning to discover patterns, trends, and other information by using text as data. Participants will develop the... Read more »

Computational Methods for Analyzing Big Data in the Social Sciences

Computational Methods for Analyzing Big Data in the Social Sciences In this workshop hosted by the Odum Institute for Research in Social Science, participants will get an overview of various aspects of computational research methods. Specifically, this session will provide a brief overview of the most frequently-used computational methods in communication and media research, as... Read more »

Biostatistics Seminar – Knowing the signs: simpler ways to think about p-values, and much else

Dr. Kenneth Rice's research focuses primarily on developing and applying statistical methods for complex disease epidemiology, notably cardiovascular disease. He leads the Data Coordinating Center and Analysis Committee for the NHLBI's TOPMed project and is the PI of the associated U01 project (HL137162). He also chairs the Analysis Committee for the CHARGE consortium, a large... Read more »

Discovering how complex traits are regulated using unsupervised learning

Barbara E. Engelhardt, an associate professor, joined the Princeton Computer Science Department in 2014 from Duke University, where she had been an assistant professor in Biostatistics and Bioinformatics and Statistical Sciences. Her research interests are Machine learning, Bayesian statistics, statistical genetics, computational biology, quantitative genetics and she received an Alfred P. Sloan Research Fellowship, 2016.... Read more »