The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying,
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Training: Introduction to Social Science Methods
December 7, 2015 to December 8, 2015
This is a two-day workshop!
Training: Introduction to Social Science Methods
December 7, 2015 to December 8, 2015
This is a two-day workshop!
Training: Advanced Linear Modeling in R
November 12, 2015
Linear modeling is the one of the most flexible methods available in inferential statistics, but this flexibility comes at a learning cost.
Training: Introduction to Pandas
November 9, 2015
"pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive." It enables "doing practic
Training: Regression Discontinuity Design - Part 3
November 9, 2015
This session is the third of a three part series on regression discontinuity designs. We will discuss common problems that arise in applied RD and how they can be overcome.
Training: Regression Discontinuity Design - Part 2
November 4, 2015
This session is the second of a three part series on regression discontinuity designs. We will discuss smoothers, bandwidth selection, confidence intervals, and covariate adjustment.
Training: Regression Discontinuity Design - Part 1
October 28, 2015
This session is the first of a three part series on regression discontinuity designs. We will cover a number of real-world examples and discuss different ways of analyzing them.
Training: Introduction to Sampling
October 20, 2015
This workshop will cover the basic principles and methods of sampling. Topics will include a discussion of the various types of samples, the creation of sampling frames, the use of stratification
Training: Finding Health Statistics
October 15, 2015
Participants in this workshop will learn about some of the issues surrounding the collection of health statistics, and will also learn about authoritative sources of health statistics and data.
