Thursday, 13 September 2012

Categorical Data Analysis

Do you work with binary, categorical, or count data?  You'd be a rare analyst if you didn't.  There are lots of details to consider - when to do exact tests, what they are, how to handle ordinal data, the role of modeling as opposed to significance testing, what to do when the assumptions required for Poisson regression fail, and much more.  Learn more in online course on "Categorical Data Analysis" (Brian Marx) at

"Categorical Data Analysis," covers the analysis of contingency table data (tabular data in which the cell entries represent counts of subjects or items falling into certain categories). Topics include tests for independence (comparing proportions as well as chi-square), exact methods, treatment of ordered data, as well as models: Poisson regression for count responses and logistic/probit regression for binomial responses. Both 2-way and 3-way tables are covered. The focus will be on interpretation of models rather than the theory behind them.  Exercises involving the use of standard statistical software are part of the course; no particular software program is required. For more details please visit at

Who Should Take This Course:
Anyone who needs to analyze data in which the response is in categorical form. Market researchers, medical researchers, surveyors, those who study education assessment data, quality control specialists, life scientists, environmental scientists, ecologists.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Overview of Categorical Responses
  • Binomial and multinomial distributions
  • Maximum Likelihood
  • Test of proportions

SESSION 2: Structure of Contingency Tables
  • Joint, marginal and conditional probabilities
  • Odds ratio and relative risk
  • Test of independence
  • Ordinal data
  • Exact testing
  • Three-way tables
  • Conditional independence and homogenous association

SESSION 3: Generalized Linear Models
  • Binary data: logistic and probit models
  • Poisson regression for count data
  • Model checking

SESSION 4: Applications and Interpretations for Logistic Regression
  • Inference
  • Categorical predictors
  • Multiple logistic regression

Dr. Brian Marx is Professor of Statistics at Louisiana State University, and has taught Categorical Data Analysis for over ten years. He is currently serving as Chair of the Statistical Modeling Society and is the Coordinating Editor of "Statistical Modeling:  An International Journal."

You will be able to ask questions and exchange comments with Dr. Brian Marx via a private discussion board throughout the course.   The courses take place online at in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at

Call: 020 66009116


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