January 11, 2016

The following qualitative data analysis workshop is being offered as part of an intensive series.  Workshop attendees are welcome to pick and choose which sessions best fit their qualitative data a

Training: INTENSIVE: Stata
January 14, 2016 to January 15, 2016

This is a 2-day intensive presentation of the D-Lab’s Introductory Stata workshop series. It will cover the following materials. 

Part I:  Introduction 

Training: INTENSIVE: Stata
January 14, 2016 to January 15, 2016

This is a 2-day intensive presentation of the D-Lab’s Introductory Stata workshop series. It will cover the following materials. 

Part I:  Introduction 

January 15, 2016

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,

January 15, 2016

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,

January 14, 2016

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,

January 13, 2016

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,

January 13, 2016

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,

January 12, 2016

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,

January 19, 2016 to January 21, 2016

This INTENSIVE offers an introduction to a range of Text Analysis approaches, including dictionary methods, classification and machine learning, TF-IDF, clustering, and topic modeling.

Pages