6 Best Books on Categorical Data Analysis

“Categorical Data Analysis (Wiley Series in Probability and Statistics)” Book Review: This book discusses the latest methods for univariate and correlated categorical multivariate responses. It covers various topics, such as smoothing, methods of regularization and methods of classification. Linear discriminant analysis, classification trees and cluster analysis are also explained in the book. This book will be beneficial for biostatisticians and researchers in the social and behavioral sciences, medicine and public health.

“Categorical Data Analysis by AIC (Mathematics and its Applications)” Book review: This book discusses a practical and unified approach to categorical data analysis. The Akaike Information Criterion (AIC) and the Akaike Bayesian Information Criterion are based on this criterion (ABIC). It covers various topics, such as the problem of categorical data variable selection, a non-parametric density estimator, and its application to non-parametric test problems. This book will be beneficial for statisticians working in mathematics, the social, behavioural and engineering.

“Applied Categorical and Count Data Analysis” Book Review: This book discusses the statistical analysis of discrete data, including categorical and count results. It covers various topics, such as contingency tables, logistic models, and models of Poisson regression. The book also describes the models for zero-modified count performance, study of reliability and methods to deal with missing values. This book will be useful for graduate and senior undergraduate students in biostatistics.

“Categorical Data Analysis (Wiley Series in Probability and Statistics)” Book Review: This book discusses the latest methods for univariate and correlated categorical multivariate responses. It covers various topics, such as smoothing, methods of regularization and methods of classification. Linear discriminant analysis, classification trees and cluster analysis are also explained in the book. This book will be beneficial for biostatisticians and researchers in the social and behavioral sciences, medicine and public health.

“Head First Data Analysis:” Book Review: A learner’s guide to big numbers, statistics, and good decisions. Today, deciphering information is a basic dynamic factor for organizations and associations. In the event that your work expects you to oversee and investigate a wide range of information, go to Head First Data Analysis, where you’ll rapidly figure out how to gather and coordinate information, sort the interruptions from reality, find significant examples, reach inferences, foresee the future, and present your discoveries to other people. Regardless of whether you’re an item designer investigating the market suitability of another item or administration, a showcasing chief measuring or foreseeing the viability of a mission, a salesman who needs information to help item introductions, or a solitary business person answerable for these information concentrated capacities and that’s only the tip of the iceberg, the remarkable methodology in Head First Data Analysis is by a wide margin the most effective approach to realize what you need to know to change over crude information into a fundamental business apparatus.

“Performing Data Analysis Using IBM SPSS” Book Review: This book discusses the statistical procedures presented with an example issue, a detailed analysis and related data sets. This involves a detailed mathematical method, an example problem or research target, along with a data set and screen shots accompanying it. It covers various topics such as IBM SPSS statistical performance, procedures for descriptive statistics, correlation of bivariates and analysis of survival.