Master 2021/2022

Categorical Data Analysis: Introductory and Advanced Topics

Type: Elective course (Comparative Social Research)

Area of studies: Sociology

Delivered by: School of Communication

Where: Faculty of Social Sciences

When: 1 year, 4 module

Mode of studies: offline

Open to: students of one campus

Instructors: Kirill Chmel

Master’s programme: Comparative Soсial Research

Language: English

ECTS credits: 5

Contact hours: 32

Course Syllabus

Abstract

In recent years the use of specialized methods for categorical data analysis has significantly increased in social science. Discrete variables have always used as standard measures in public opinion surveys and experimental studies. However, they also require methods that account for properties of probability distributions for categorical data. We will start our course with basics like contingency tables, and then move on to the modelling of binary, multinomial ordered and unordered outcomes. Such advanced topics as maximum likelihood estimation and optimization methods will be covered upon request. At the end of this course students will be able to conduct categorical data statistical analysis using the freeware package R and give a substantive interpretation of results.