Course 6 Categorical Data Analysis
Categorical data analysis (a.k.a. Discrete analysis) is a crucial area in statistics that deals with data with qualitative or discrete outcomes rather than continuous. This type of data often involves variables that represent categories, such as gender, ethnicity, or survey responses, which can be analyzed using a variety of methods to understand relationships, patterns, and associations between variables. The categorical data analysis requires specialized techniques, such as contingency tables, chi-square tests, and logistic regression, to model the dependencies between variables and make inferences about the underlying processes. Understanding these methods is vital for researchers across many fields, including social sciences, medical research, and marketing, as it enables them to interpret and make decisions based on categorical information.