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2016 Winter Workshop

The winter workshop is a supplement to the annual summer workshop. Two courses will be offered, one on introductory topics and the other on advanced topics. 

Registration:

Registration available here.

Workshop Schedule:

Monday, January 11: Introduction to R  (10 a.m. - 3:30 p.m.)

Wednesday, January 20: Machine Learning (3 p.m. - 8 p.m.)

Location:

The Institute for Research in the Social Sciences at 30 Alta Road, Stanford

Cost:

$30 per day. Price includes food.

Introduction to R Synopsis

Instructors: Gustavo Robles and Jonathan Mummolo

Morning Session:

  • Introduction to R
  • R Basics: Workspace, working directory, and scripts
  • Creating and storing objects
  • Functions in R
  • R-Packages (code, functions, and datasets)
  • Reading and exporting data

Afternoon Session: Reading and Manipulating Data

  • Selecting and subsampling data.
  • Transforming data.
  • Merging and appending datasets.
  • Loops in R

*Please come prepared to follow along on your laptop.

R program download links:

Some useful books:

  • Maindonald, John, and W. John Braun (2010). “Data Analysis and Graphics Using R”. Cambridge University Press.
  • Fox, John, and Sanford Weisberg (2011). “An R Companion to Applied Regression”. SAGE Publications, Inc.

Machine Learning Synopsis

This workshop is an introductory-level overview of machine learning concepts for students without previous exposure to the field. We will survey some of the important elements of supervised learning, and some unsupervised learning methods are discussed. Students will work on hands-on exercises in R (Advanced knowledge of R programming is a pre-requisite).

 

The following topics will be discussed in varying levels of details:

  • Introduction to statistical learning, model selection and regularization methods (ridge and lasso)
  • nonlinear models, tree-based methods, random forests
  • support-vector machines (briefly), and clustering (k-means and hierarchical)

 

Requirements: Advanced knowledge of R programming and basic statistics. Please bring a laptop computer running R on any supported operating system.

 

Instructor bio: Bruno Abrahao is a Postdoctoral Scholar in Sociology at Stanford University. He holds a Ph.D. in Computer Science from Cornell University, and his research interests are motivated by addressing Sociological questions using large datasets.