Categorical data analysis methods and applications

In this study, Categorical Data Analysis methods which has been popular in last decade, is investigated. Firstly, ?Categorical Data? notion is given, and statistical distributions about categorical data and contingency tables is explicated. Also, relative risk, odds and odds ratio notions whis is used in contingency tables are given. In two-ways contingency tables, Pearson?s chi-square statistics is enough for statistical inferences but can?t used in bigger contingency tables. For determining association structures in three-ways or bigger contingency tables, ?Log-Linear Models? is discussed which doesn?t discriminate variables as dependent or independent. Interactions between many variables can be interrogated with log-linear models whis is classified as hierarchical and non-hierarchical. Also, ?Logistics Regression Analysis? is disscussed which can take a categorical data as a dependent variable.