Introduction to categorical data analysisChapters 1 through 7, which cover basic chi-square tests, associativity measures, logistic regression models, and log linear models most commonly used in categorical data analysis, are included in lectures for the first semester of the third and fourth years of undergraduate study, Will be appreciated if they select and lecture according to their major field of study. The content of Chapters 10 and 11, which is a more complex statistical analysis of categorical data analysis, may be particularly useful for graduate students and researchers.
Perfectly fine. Like many of these textbooks, it is plagued by toy problems which don’t give you an understanding of how to use the ideas. Projects with messy datasets in the back and open ended responses would be ideal, but I suppose that is why we have Kaggle.