FCAP Workshops 2009

Friday, May 1, 2009
9:00 AM – 4:00 PM  
Fordham University Rose Hill Campus
Bronx, New York  

$125 for the workshop of your choice (workshop materials and lunch included)

Note: a $10 cash-only parking fee will be charged to those who elect to park on-campus.

Click here to register

Click here for information on hotels and accomodations

Bayesian Analysis with WinBugs

Matthew Johnson, Ph.D.
Associate Professor of Statistics and Education, Teachers College
http://www.tc.columbia.edu/faculty/index.htm?facid=msj2119

The first portion of this workshop will introduce participants to the basic concepts required for Bayesian data analysis. Topics will include the statistical model, prior and posterior distributions, Directed Acyclic-Graphs, and Bayesian inference. These topics will be illustrated using the normal and/or binomial distributions. After this general introduction, the workshop will introduce participants to the basics of Markov chain Monte Carlo (MCMC) and WinBugs. Specifically, topics will include an overview of MCMC, the most common algorithms, using WinBugs (syntax and the Doodle utility), and output analysis (monitoring convergence, point estimates, posterior variance and standard deviation, approximating credible intervals). These topics will be illustrated using the same simple examples from the first portion of the workshop as well as a simple normal measurement error model.

In this workshop participants will develop Bayesian models for a number of popular models from psychometrics, and then use WinBugs to approximate the posterior distributions of the model parameters. Models for discussion will include models for paired comparisons, IRT models, unfolding models, latent class and mixture models and factor analysis models. After the discussion and implementation of Bayesian psychometric models in WinBugs, some advanced MCMC topics will be discussed. Possible topics for discussion will include approximating Bayes factors with MCMC output and goodness of fit and model checking with posterior predictive checks.

Introduction to Computing in R

John Verzani, Ph.D.
Professor and Chair of Mathematics, CUNY/College of Staten Island
http://wiener.math.csi.cuny.edu/verzani
Author of: Using R for Introductory Statistics and Simple R

John Verzani is Professor and Chair of the Department of Mathematics at CUNY's College of Staten Island. He is a long time R advocate and author the book "Using R for Introductory Statistics."

This hands-on workshop will provide a basic introduction to R targeted at non- or new-R users. By the end of the day, participants should have seen enough to understand some of what R can do, and how it does it. The session is geared around doing basic statistics in R and deal with some of the programming aspects of R that can bewilder new users. The planned presentations will involve some lecture time and some lab time to try-out the lecture material.