Statistics 597T - ST- Analysis of Discrete Data

Spring
2023
01
3.00
Daeyoung Kim

M W F 12:20PM 1:10PM

UMass Amherst
69027
Lederle Grad Res Ctr rm A203
dkim1@umass.edu
Discrete/Categorical data are prevalent in many applied fields, including biological and medical sciences, social and behavioral sciences, and economics and business. This course provides an applied treatment of modern methods for visualizing and analyzing broad patterns of association in discrete/categorical data. Topics include forms of discrete data, visualization/exploratory methods for discrete data, discrete data distributions, correspondence analysis, logistic regression models, models for polytomous responses, loglinear and logit Models for contingency tables, and generalized linear models. This course is primarily an applied statistics course. While models and methods are written out carefully with some basic mathematical derivations, the primary focus of the course is on the understanding of the visualization and modeling techniques for discrete data, presentation of associated models/methods, data analysis, interpretation of results, statistical computation and model building.

STATISTC 525

Permission is required for interchange registration during the add/drop period only.