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 Statistis.com.
"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 http://www.statistics.com/categorical1/.
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 statistics.com 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 statistics.com accepts registration for its courses at special
prices in Indian Rupees through its partner, the Center for eLearning and
Training (C-eLT), Pune.
Call: 020 66009116
Websites:
No comments:
Post a Comment