Probability Distributions: With Truncated, Log and Bivariate

In this review of Probability Distributions: With Truncated, Log and Bivariate Extensions, the bottom line is clear: this compact reference is for researchers and applied statisticians who need worked examples and tables for less common distributions. The author delivers a focused, practical guide that fills gaps left by standard texts, especially for truncated normal and bivariate lognormal cases. Readers seeking quick access to table values and application examples will find the volume immediately useful; it is not, however, a beginner's textbook on probability theory.

Key Features

• Concise overview: Summarizes commonly used continuous and discrete distributions so readers get a quick refresher before diving into the specialized material.
• Uncommon distributions explained: Covers discrete normal, left- and right-partial, and other less familiar forms with examples that show practical use.
• Truncated normal detail: Describes left-truncated and right-truncated normal shapes and behavior, enabling applied users to model data that deviate from symmetry.
• Bivariate extensions: Presents the bivariate normal and bivariate lognormal with examples useful for multivariate modeling and sample analysis.
• Table values with examples: Includes tables and worked examples so researchers can apply distributions directly to sample data without deriving values from scratch.

Who It's For

This book is best for practicing statisticians, engineers, and applied researchers who need quick, practical guidance on distributions that are not well covered elsewhere. Graduate students working on applied projects will also find the worked examples and tables handy when they need usable numbers rather than lengthy derivations.

Those looking for an introductory or theoretical textbook on probability foundations should look elsewhere; this volume assumes familiarity with core distribution concepts and emphasizes application over pedagogical exposition.

Pros & Cons

Pros

• Focuses on less common distributions, filling a niche left by standard references.
• Provides table values and step-by-step examples that speed up real data work.
• Includes both univariate and bivariate treatment, aiding multivariate analysis tasks.

Cons

• Not a beginner's primer; readers need prior familiarity with basic probability concepts.

Specifications

Title	Probability Distributions: With Truncated, Log and Bivariate Extensions
Author	Nick T. Thomopoulos
Scope	Continuous, discrete, truncated, lognormal, and bivariate distributions
Includes	Worked examples and table values for applied use
Target audience	Researchers, applied statisticians, graduate students
Special topics	Discrete normal, left/right-partial, truncated normals, bivariate lognormal

Our Verdict

Probability Distributions: With Truncated, Log and Bivariate Extensions is a focused, practical resource for applied users who need ready access to table values and worked examples for uncommon distributions. It represents good value for researchers who model truncated or bivariate data and prefer concrete application over extended theory.

Frequently Asked Questions

Does this book include numerical tables?
Yes, the book provides table values accompanied by examples so readers can apply the distributions to sample data.

Is it suitable for beginners?
Not really; the book assumes familiarity with basic distribution concepts and is aimed at applied users and researchers.

Are bivariate distributions covered?
Yes, both the bivariate normal and bivariate lognormal are described with practical examples for multivariate analysis.