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Elsevier

Discrete Choices

A Comprehensive Guide to Distributions and Inference for Categorical Data

  • 1st Edition - March 1, 2027
  • Latest edition
  • Authors: Jiju Gillariose, Joshin Joseph, Christophe Chesneau
  • Language: English

Discrete Choices: A Comprehensive Guide to Distributions and Inference for Categorical Data provides a unified and modern treatment of probability, inference, and modeling for ca… Read more

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Description

Discrete Choices: A Comprehensive Guide to Distributions and Inference for Categorical Data provides a unified and modern treatment of probability, inference, and modeling for categorical and discrete data. Although categorical outcomes are ubiquitous across statistics, data science, economics, epidemiology, and the social sciences, existing resources often treat these topics in fragmented ways, separating probability theory, inference, diagnostics, and applications into distinct texts. This book addresses that gap by presenting a coherent framework that begins with probability foundations and sampling theory, develops classical and hierarchical discrete distributions, and advances to modern likelihood-based and Bayesian inference. Core topics include Bernoulli, Binomial, Multinomial, and Poisson models; compound distributions such as the Beta–Binomial and Dirichlet–Multinomial; resampling methods; model diagnostics; and principled model selection. Advanced chapters extend this framework to high-dimensional categorical data, compositional data, network and relational structures, causal inference with multi-valued treatments, and fairness and bias diagnostics in categorical prediction. Extensive case studies and interactive hands-on data labs illustrate real-world applications in health, the social sciences, marketing, and text analytics, emphasizing reproducible and applied workflows.

Balancing theoretical rigor with practical relevance, Discrete Choices: A Comprehensive Guide to Distributions and Inference for Categorical Data is suitable both as a graduate-level textbook and as a professional reference for researchers and practitioners working with discrete data.

Key features

  • Introduces a clear and didactic understanding of essential concepts in statistics and data science, including categorical data and statistical inference
  • Includes numerous illustrations of theoretical concepts and worked examples, which provide explanations and additional context
  • Aligns with commonly offered upper-level courses in statistics, data science, and related topics in the field
  • Serves as a valuable resource for students and instructors and as solid foundational material with a unified approach for early-stage researchers
  • Offers ancillary support, including an Instructor’s Solutions Manual and additional R and Python programming study resources for students

Readership

Upper-level undergraduate and graduate students majoring in statistics, data science and management, or related fields

Table of contents

Part I Foundations and Core Methods

1. Foundations of Categorical Data

2. Core Distributions for Discrete Outcomes

3. Hierarchical & Conjugate Families

4. Statistical Inference

5. Model Diagnostics and Selection

Part II Advanced Topics and Applications

6. Advanced and Emerging Topics

7. Applications Across Fields

8. Categorical Treatments and Fairness in Prediction

9. Case Studies and Data Labs

Product details

  • Edition: 1
  • Latest edition
  • Published: March 1, 2027
  • Language: English

About the authors

JG

Jiju Gillariose

Jiju Gillariose holds a PhD in Statistics from Mahatma Gandhi University, a public university in India. She served as an Assistant Professor and Research Guide in the Department of Statistics and Data Science at CHRIST (Deemed to be University), Bangalore, India, from 2021 to 2026. She is currently working as an Assistant Professor at St. Teresa’s College, Ernakulam. Her areas of expertise include Distribution Theory, Estimation Theory, Survival Analysis, Reliability Theory, Data Analytics, and Applied Statistics. Dr. Gillariose has authored over 50 research articles in reputed peer-reviewed journals. She was awarded the INSPIRE Fellowship by the Department of Science and Technology, Government of India, and has also received project funding from the Indian Council of Social Science Research (ICSSR) as a Principal Investigator.

Affiliations and expertise
Assistant Professor, St. Teresa’s College, Ernakulam,, India

JJ

Joshin Joseph

Joshin Joseph received his PhD in Commerce from Mahatma Gandhi University, India. He is currently serving as an Assistant Professor in the School of Commerce and Professional Studies at Marian College Kuttikkanam (Autonomous), Kerala. His areas of expertise include Human Resource Management, Data Analytics, Work-Life Balance, Employee Psychology, and Statistical Analysis. Dr. Joseph has authored over forty research articles in reputable peer-reviewed journals and contributed several book chapters. He has cleared the UGC-NET and was awarded the Junior Research Fellowship (JRF) by the University Grants Commission (UGC), Government of India. He has also received

project funding from the Indian Council of Social Science Research (ICSSR). Additionally, he holds copyrights for multiple scholarly works.

Affiliations and expertise
Assistant Professor, School of Commerce and Professional Studies at Marian College Kuttikkanam (Autonomous), Kerala, India

CC

Christophe Chesneau

Christophe Chesneau holds the distinguished position of "exceptional class" associate professor at the University of Caen-Normandie, France. With an extensive teaching career exceeding 20 years, his specialization lies in the areas of probability and statistics, with an emphasis on practical applications through the use of R software. Teaching is a primary passion for him, evident in his role as a responsible figure for the first year of the master's degree "Applied Statistics and Decision Analysis" over the last six years. Beyond his teaching commitments, Christophe Chesneau is the author of five books in French on probability and statistics, demonstrating his commitment to disseminating knowledge. In addition to conventional teaching, he generously shares his expertise through freely accessible online courses. His prolific research encompasses mathematics, probability, statistics, and applied data analysis, with more than 500 articles in esteemed international journals. In particular, he contributed significantly to the development of two R packages, solidifying his impact on statistical software tools. Additionally, Christophe Chesneau is a distinguished member of several editorial boards for prestigious journals, further highlighting his influential contributions to the field of probability and statistics.
Affiliations and expertise
University of Caen-Normandie, France