We have compiled the list of Best Reference Books on Probability subject. These books are used by students of top universities, institutes and colleges. Here is the full list of best books on Probability along with reviews.
Kindly note that we have put a lot of effort into researching the best books on Probability subject and came out with a recommended list of best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on “Probability” as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
List of Probability Books with author’s names, publishers, and an unbiased review as well as links to the Amazon website to directly purchase these books.
 Introduction to Probability and Random Processes
 Introduction to Probability Theory
 Advanced Probability Theory
 Probability and Statistics
 Probability, Random Process and Statistical Inference
 Probabilistic Models
1. Introduction to Probability and Random Processes
1. “Conditional Independence in Applied Probability” by P Pfeiffer
Book Review: The book demonstrates various theories and applications that are needed for a thorough understanding of probability. The book contains many exercises and real life examples in the fields of biology, computer science, cryptology, ecology, public health, sports and many more. The book stresses more on simulation and demonstrates computational and theoretical results. The book contains chapters on conditional probability, independent trials, random variables, discrete and continuous distributions, continuous probability and many more. The book also contains many problems of probability and numerous practical examples. This book is suitable for undergraduate courses in the field of probability.


2. “Probability and computing: Randomized Algorithms and Probabilistic Analysis” by Mitzenmacher and E Upfal
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“Probability and computing: Randomized Algorithms and Probabilistic Analysis” Book Review: This book provides a detailed overview on probability and computing. It talks about randomized algorithms and probabilistic analysis. It covers applications ranging from machine learning and combinatorial optimization to communication networks and secured protocols. It is designed focusing on courses of beginning graduate and advanced undergraduate students in computer science and applied mathematics. It gives an amazing introduction to the probabilistic techniques and different paradigms used in development of probabilistic algorithms and analyses. The book provides numerous examples and applications.


3. “Introduction to Probability” by D Bertsekas and J Tsitsiklis
Book Review: This book provides very nice introduction to probability theory, stochastic processes and probabilistic models used in the field of science, engineering, economics and many other fields. This book is a very good textbook on probability at the graduate and undergraduate levels. The book covers the basics of probability theory which include probabilistic models, discrete and continuous random variables, limit theorems, least squares estimation, bivariate normal distribution, Bernoulli, Poisson and Markov processes and many more.


4. “Probability, Random Variables, and Random Processes” by John J Shynk
“Probability, Random Variables, and Random Processes” Book Review: This book provides a comprehensive overview on probability theory. It provides a rigorous mathematical framework required for random variables and random processes. It has features like several appendices including related material on integration, inequalities and identities, frequency domain transforms, and linear algebra. It has statistics covered in detail, along with their connection to parameter estimation techniques. It is designed to focus on students and teachers to cover topics like engineering like communication systems and information theory, adaptive filtering, optimal filtering, and antenna beamforming.


5. “Probability and Random Processes” by S Palaniammal
“Probability and Random Processes” Book Review: This book provides a comprehensive overview on probability and random processes. It provides the fundamental concepts and realworld applications of probability and random processes. It begins with explanation of probability theory; followed by analyzing various types of random processes. It also discusses in detail the random variables, correlation, standard distributions, and spectral densities. The topics are in wellorganized sequence with appropriate explanations along with simple mathematical formulas. This book is designed to focus on students and teachers of various engineering and technology like Computer Science and Engineering, Electronics and Communication Engineering, Biomedical Engineering, and Information Technology.


6. “Theory of Probability and Random Processes” by Leonid B Koralov and Yakov G Sinai
“Theory of Probability and Random Processes” Book Review: This book provides a fundamental overview on theory of probability and random processes. It provides a detailed and selfcontained explanation of classical probability theory and theory of random processes. It includes a comprehensive discussion of Lebesgue integration, random walks, laws of large numbers, Markov chains, limit theorems, and its relation to renormalization group theory. It also covers the theory of stationary random processes, Brownian motion and generalized random processes.
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7. “Probability Theory, Random Processes and Mathematical Statistics” by Y Rozanov Rozanov
“Probability Theory, Random Processes and Mathematical Statistics” Book Review: This book provides a comprehensive overview on probability theory, random processes, and mathematical statistics. It covers important areas of modern mathematics and their applications. It helps develop rigorous models for appropriate treatment for various random phenomena which are encountered in the real world. It provides numerous tools for analysis, prediction, and control of random phenomena. This book is designed to focus on students and teachers of various courses in undergraduate and graduate level courses.


8. “Probability, Random Processes, and Statistical Analysis” by Hisashi Kobayashi Brian L Mark William Turin
“Probability, Random Processes, and Statistical Analysis” Book Review: This book provides a detailed overview on probability, random processes, and statistical analysis. It presents a broad range of advanced topics and their applications. It provides a vast coverage of Bayesian vs. frequentist statistics, spectral representation, inequalities, time series and bound and unbound approximation, maximum likelihood estimation and the expectation maximization algorithm, and geometric Brownian motion. It talks about applications such as Markov models, and Baum Welch algorithms, algorithms for machine learning, queueing, Wiener and Kalman filters, and loss networks are covered in detail.


9. “Probability and Random Processes for Electrical and Computer Engineers” by John A Gubner
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“Probability and Random Processes for Electrical and Computer Engineers” Book Review: This book provides a fundamental overview on probability and random processes. It describes probability as a powerful tool which helps engineers to explain, model, analyze, and design technology. It assumes basic knowledge of probability and explains more complex topics which are required at graduate level. The first few chapters cover the basics of probability and discrete and continuous random variables. The later chapters have specialized coverage, including Gaussian random vectors, random vectors, random processes, convergence, and Markov Chains.


10. “Schaum’s Outline of Probability, Random Variables, and Random Processes” by Hwei P Hsu
“Schaum’s Outline of Probability, Random Variables, and Random Processes” Book Review: The book aims at presenting all the important processes and concepts underlying probability. The chapters of this book are comprehensive, precise, and explain each concept in proper steps. This book provides a fundamental overview on probability, random variables, and random processes. It describes all the major topics related to probability, random variables, multiple random variables, limit theorem, random processes, analysis, and processing of random processes, estimation theory, decision theory, queuing theory, and information theory. It includes more than 400 solved problems, examples, and practice exercises to enhance your problemsolving skills. It provides reader access to detailed videos featuring instructors who explain the most useful problems. It discusses topics like Gaussian random vectors, random vectors, random processes, convergence, and Markov Chains. It has everything needed to build confidence, skills, and knowledge for scoring good grades. The technique of effective problemsolving is introduced in this text. The content of this book is supported by many solved and unsolved problems. The applications of probability in various fields are mentioned in this text. The book consists of several examples and exercises.


11. “Introduction to Measure and Probability” by K R Parthasarathy
“Introduction to Measure and Probability” Book Review: The book is an excellent blend of aesthetic and practical aspects of measure and probability. The chapters of this cover all the major topics related to probability on Boolean algebra, extension of measures, borel maps, integration, measures on product spaces, Hilbert space, weal convergence of probability measures, and invariant measures on groups. The theorem and proofs are described efficiently. For better understanding of the readers, the book contains many exercises and examples. The book will be useful for the undergraduate and graduate students seeking knowledge in measure theory and probability theory.


12. “Probability, Reliability and Statistical Methods in Engineering Design” by Haldar A and Mahadevan S
Book Review: The book presents the fundamentals of reliability and statistics that is needed for risk based engineering analysis and carries out clear presentation of design. The book also contains numerous examples that explain the risk based design concepts in the field of reliability and statistics. The book covers many concepts and skills that are needed for reliability assessments. The book also presents many reliability assessment methods and concepts that are needed for risk based design implementation in practical problems. The book also explains risk based and deterministic design concepts.


13. “Convergence of Probability Measures” by P Billingsley
“Convergence of Probability Measures” Book Review: This is an easy to read textbook that incorporates all the topics essential for detailed knowledge of the subject and has a straightforward approach and is readerfriendly. This book is updated with classic work Convergence of Probability Measures to reflect developments of the development of the subject. This book brings a clear, precise, uptodate account of probability limit theory in metric spaces. This book consists of many examples that illustrate the power, applications and utility of this theory in various disciplines such as statistics, engineering, economics, and population biology along with smooth transition and keeping the simplicity of the subject. This book covers topics like Weak Convergence in Metric Spaces, The Space C & D, Dependent Variables, Other Modes of Convergence, etc along with appendices, problems, Bibliographical Notes, Bibliography.


2. Introduction to Probability Theory
1. “Probability and Measure” by P Billingsley
“Probability and Measure” Book Review: This book gives an integrated introduction to measure theory and probability. This book covers the latest areas in the topic and is highly updated with a new style and format, but with reliable content. This book covers the foundation of measure theory and probability with a unique writing style. This book is written in a user friendly language and is easy to read. Theory of this book is illustrated clearly with real life situations. The book has many problems with corresponding, intensive notes and with clear solutions. This book covers topics like. Probability, Measures, Integration, Random Variables and Expected Values, Convergence of distribution, Derivatives and conditional probability, Stochastic Processes, Brownian Motion, Kolmogorov’s Existence Theorem, Martingales, Conditional Probability & Expectation, etc. Along with many appendices and problematic notes for better understanding. This book also deals with stochastic processes. This book provides bibliography and list of symbols at the end of the book.


2. “Introduction to Probability” by P G Hoel
“Introduction to probability theory” Book Review: This book discusses probability spaces, combinatorial analysis, discrete random variables and expectation of discrete random variables. This book also explains about continuous random variables, jointly distributed random variables and expectations and the central limit theorem. It also deals with moment generating functions, characteristic functions, random walks and poisson processes.


3. “A First Look at Rigorous Probability Theory” by J S Rosenthal
“A First Look at Rigorous Probability Theory” Book Review: This book is a concise introduction to probability theory using measure theory. The text in the book is simple and provides complete proofs of all the essential introductory results. The book Focus on measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. The book has exercises and additional topics for better overview of the topic. The book is for graduate students from a wide variety of fields like mathematics, statistics, economics, management, finance, computer science, and engineering. This book covers topics like The need for measure theory, Probability triples, Further probabilistic foundations, Expected values, Inequalities and convergence, Distributions of random variables, Stochastic processes and gambling games, Discrete Markov chains, More probability theorems, Weak convergence, Characteristic functions, Decomposition of probability laws, Conditional probability and expectation, Martingales, General stochastic processes, etc. This book is designed for graduate and Ph.D students of engineering, economics and management.


4. “Probability with Applications” by M Woodroofe
“Probability with Applications” Book Review: This book explains the classical model, axiomatic probability, conditional probability and independence. This book also deals with binomial probabilities, random variables, random vectors, distribution theory and limit theorems.


5. “An Introduction to Probability Theory and its Applications” by William Feller
“An Introduction to Probability theory and its Applications” Book Review: This book starts with the explanation of nature of probability theory. This book covers sample space, elements of combinatorial analysis, fluctuations in coin tossing and random walks, combination of events and combination probability. It also deals with binomial and poisson distributions, markov chains, time dependent stochastic processes. This book provides problems with solutions at the end of each chapter.


6. “An Introduction To Probability Theory” by Das  
7. “An Introduction to Probability Theory and Mathematical Statistics” by Vijay K Rohatgi
“An Introduction to Probability Theory and Mathematical Statistics” Book Review: This book is divided into three parts. This book gives an overview of probability theory and mathematical statistics. This book has nearly 550 problems with solutions and 350 worked examples and 200 remarks. This book is designed for upperundergraduate and graduatelevel students whose major is probability and statistics.


8. “An Introduction to Statistical Learning: with Applications in R” by Gareth James and Daniela Witten
“An Introduction to Statistical Learning: with Applications in R” Book Review: This book starts with the explanation of statistical learning. This book covers linear regression, classification, resampling methods, linear model selection and regularization and moving beyond regularity. It also explains about treebased methods, support vector machines and unsupervised learning. It also has exercises at the end of each chapter.


9. “An Introduction to Probability Theory and Its Applications Vol 2” by William Feller  
10. “A Natural Introduction to Probability Theory” by R Meester  
11. “An Introduction to Probability Theory and its Applications” by W Feller
“An Introduction to Probability Theory and its Applications” Book Review: The book starts with the background and nature of probability theory, Moving further the topics like sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, and stochastic processes are described in detail. To give better practical knowledge and relatable content to the readers many realworld applications of probability theory are also included in this book.


12. “Probability Essentials” by Jean Jacod and Philip E Protter
Book Review: This book is very useful at the graduate level for the courses on probability theory. It is very beneficial for students and teachers in the field of finance theory, electrical engineering and operations research. The book also contains a dedicated chapter on martingale theory and certain advanced topics like Brownian motion, calculus and statistical inference. The book contains around 28 chapters and the prerequisite is basic knowledge of mathematics.


13. “Probability Measures on Metric Spaces” by K R Parthasarathy
“Probability Measures on Metric Spaces” Book Review: Throughout the book, the theory is well presented, allowing students to have a deep dive of the topic. This book generally covers separable metric groups, locally compact abelian groups, Hilbert spaces, and the spaces of continuous functions. This book is divided into seven chapters which are the Borel Subsets of a Metric Space, Probability Measures in a Metric Space, Probability Measures in a Metric Group, Probability Measures in Locally Compact Abelian Groups, the Kolmogorov Consistency Theorem and Conditional Probability, Probability Measures in a Hilbert Space, Probability Measures on C[0, 1] and D[0, 1]. Each chapter starts with an introduction and covers the rest of the chapter. This book begins with an overview of isomorphism theorem and then deals with tightness, regularity, and perfectness of measures defined on metric spaces. This book is for those who are into the topic and for staticians.


14. “Theory of Probability” by Parimal Mukhopadhyay
“Theory of Probability” Book Review: This book provides a systematic exposition of the theory which contains a balanced mixture of the classical approach and the modern day axiomatic approach. This book covers univariate distributions, bivariate normal distributions, multinomial distribution and convergence of random variables. This book provides explanatory notes, examples and exercises. This book is designed for students who have a simple knowledge of mathematics at graduate level. This book has worked out examples and exercises with hints.


15. “Probability Theory: The Logic of Science” by E T Jaynes and G Larry Bretthorst
“Probability Theory: The Logic of Science” Book Review: This book is divided into two parts. First part deals with principles and elementary applications. Second part deals with advanced applications. This book is designed for readers with a knowledge of applied mathematics at an advanced undergraduate or higher level. This book discusses applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. This book has many exercises and problems.


16. “Probability concepts in Engineering Planning and Design” by A H S Ang and W H Tang
Book Review: This book discusses the methodologies and concepts that are used to evaluate uncertainty significance in the area of system performance and design. The book also discusses the concepts of probability and statistics that is used for quality control processes. The book also discusses practical concepts and probability applications related to engineering. The book is suitable to engineers who require a working knowledge of the basic concepts of probability. The book also contains numerous problems and solutions to them.


17. “Applied Statistics and Probability for Engineers” by Douglas C Montgomery and G C Runger
Book Review: This book presents a practical approach to chemical sciences, physical sciences and engineering. This is very good textbook for courses in probability and statistics. The book stresses on real engineering applications and real engineering solutions and also includes material on bootstrap, P value usage, equivalence testing, p values combination and contains numerous examples on the same.


3. Advanced Probability Theory
1. “A Course in Probability Theory” by K L Chung
“A Course in Probability Theory” Book Review: This book is a successful tool for instructors and students alike and is a good supplement for the subject. The text is very flexible, offering instructors on the syllabus along with a proper guidance. The book has many examples which are well illustrated and explained including some special cases, the reader will have a good understanding of the topic after going through the numericals. The book covers topics like Distribution function, Measure theory, Random variable Expectation Independence, Convergence concepts, Law of large numbers Random series, Characteristic function, Central limit theorem and its ramifications, Random walk, Conditioning Markov property Martingale, Measure and Integral etc.


2. “Advanced Probability Theory” by Janos Galambos
“Advanced Probability Theory” Book Review: The context here is wrapped up with simple words and with a detailed understanding of all the key topics. This book covers all the concepts thoroughly from it’s fundamentals to advanced applications. The books cover topics in the theory of stochastic processes, expectation and integral, martingales, weak and strong convergence, conditional exceptions, transforms of distribution, independent and identically distributed random variables, infinite sequences of independent random variables, infinitely divisible distributions, weak convergence, triangular arrays of independent random variables along with hints and solutions for exercises.


3. “Probability Theory: A Concise Course” by Y A Rozanov
“Probability Theory: A Concise Course” Book Review: This book offers an excellent overview of the theory and outlook of the topic. Reader here requires some knowledge of mathematics after which the reader will find it interesting. This book provides a good treatment to the subject together with numerous applications. This book is resourceful, readable, fastmoving, and is selfcontained. The book begins with basic concepts and moves on to combinations of topics like dependent variables, events. This book deals with topics like Probability and Relative Frequency, Rudiments of Combinatorial Analysis, Elementary Events. The Sample Space, The Addition Law for Probabilities, Conditional Probability, Statistical Independence, Discrete and Continuous Random Variables. Distribution Functions, Mathematical Expectation, Chebyshev’s Inequality. The Variance and Correlation Coefficient, Bernoulli Trials. The Binomial and Poisson Distributions, The De MoivreLaplace Theorem. The Central Limit Theorem, Transition Probabilities, Persistent and Transient States, Limiting Probabilities.Kolmogorov Equations, Stationary Distributions, Definitions. Sojourn Time, More on Limiting Probabilities. Appendices along with problems at the end of each topic.


4. “Real Analysis and Probability” by R M Dudley
“Real Analysis and Probability” Book Review: This book tries to teach both the subjects with the same treatise.The text at graduate level gives the introduction measure and integration theory along with functional analysis. In this book the connections of the texts bring the subjects to real life with an interplay between the properties of metric spaces and probability measures. This book covers topics like Foundations: set theory, General topology, Measures, Integration, Lp spaces: introduction to functional analysis, Convex sets and duality of normed spaces, Measure, topology, and differentiation, Introduction to probability theory, Measurability, Stochastic processes, Convergence of laws on separable metric spaces, Conditional expectations and martingales, Convergence of laws and central limit theorems, etc. This book has enough numericals along with their solutions chapter wise.


5. “Probability Theory: An Advanced Course” by Vivek S Borkar
“Probability Theory: An Advanced Course” Book Review: The book offers a selective approach to topics from probability theory. The book is useful to someone planning to pursue research in the modern theory of stochastic processes. The book has a prerequisite of good mathematical knowledge in particular to have a basic knowledge on probability theory. The book begins with the rapid overview of the basics. Each chapter of the book deals with the topic in detail like Spaces of Probability Measures, Conditioning and Martingales, Basic Limit Theorems, Markov Chains, Foundations of ContinuousTime Processes, Conditioning and Martingales, Conditional Expectations, Strong Law of Large Numbers, Central Limit Theorem, Markov Chains, Stationary Distributions, Transient and Null Recurrent Chains, Separability and Measurability, Skorohod’s Theorem, Monotone Class Theorems, Random Variables, etc along with additional exercises at the end of each chapter.


6. “Random Processes: Filtering, Estimation and Detection” by Lonnie C Ludeman
“Random Processes: Filtering, Estimation and Detection” Book Review: This book deals with the major aspects of principles and applications of random processes which focuses on Filtering, Estimation and Detection. For several areas in engineering, an understanding of random processes is important, including information theory, computer vision, digital signal processing in electrical and computer engineering, and vibration theory and stress analysis in mechanical engineering. Critical tasks required in the study and design of modern communications technologies and valuable signal processing algorithms are the screening, measurement and identification of random processes in noisy environments. Random Processes: The fundamentals of probability and random processes are easily demonstrated by filtering, calculation, and identification, and current detection and estimation theory is comprehensive to accomplish these tasks. There are primary and interrelated subjects addressed in the text such as Random variables and random processes probability and characterizations, Optimal principle of estimation, namely the Wiener and Kalman filters, Theory of detection for both isolated and continuous time measurements.


4. Probability and Statistics
1. “Introduction to Probability and Statistics” by J S Milton and J C Arnold
“Introduction to Probability and Statistics” Book Review: The book contains the illustrations of introduction to basic probability theory and statistical inference, with a unique balance of theory and methodology in the form of diagrams to make the topic more understandable. Keeping in mind the latest syllabus of various universities in India, topics like a practical approach to methods of statistical modelling and data analysis are included in this book and a detailed description is also provided by the author. A large number of solved numerical examples drawn from various university examinations have been given at the end of the theoretical part of each chapter.


2. “Miller and Freund’s Probability and Statistics for Engineers” by R A Johnson and C B Gupta
“Miller and Freund’s Probability and Statistics for Engineers” Book Review: This book is mainly designed for engineering students and teachers. It gives an introduction to probability and statistics. It provides computer exercises for MINITAB to get familiarized with this software. It explains graphs of the sampling distribution to show the critical region and pvalue. It includes accessible discussion on joint distributions and the properties of expectations. It covers the balanced presentation of applications and theory widely. Also contained in it are exam patterns and latest research results which will give a wider scope for preparation. The book covers various concepts in it’s subsequent chapters on topics like basic concepts of Probability, Statistics and Random Variable. Advanced concepts like basic concepts of Probability, Statistics and Random Variable are also covered in the book. Each chapter contains various descriptions, examples, laws and important points in order to make the revision easier. It contains summary tables of testing performance which provides a reference for students. Each chapter contains a checklist of key terms and statistical guidelines to apply procedures.


3. “Probability and Statistics for Engineers and Scientists” by Walpole R E
“Probability and Statistics for Engineers and Scientists” Book Review: This book is targeted for undergraduate level students and the concepts are explained in a simple and concise manner. The points are covered in a logical way, and there are a wide range of solved examples given in the book. It’s main focus lies on Applied problems. Topics like introduction to basic probability theory and statistical inference, with a unique balance of theory and methodology and various problems dealing with are dealt in this book. Diagrams provided in this book are clear and error free. There are standard and simple procedures used for deriving equations and it contains ample number of solved examples. This book is mainly for chemical as well as mechanical engineering students.


4. “Statistics for Engineers and Scientists” by Navidi W
“Statistics for Engineers and Scientists” Book Review: This textbook deals with the practical approach to methods of statistical modeling and data analysis so that the subject is perceived by the student as both a science and an art. The theories and explanations are supported by a large number of solved examples. Additional figures have also been added for the clarity and understanding of the book. Multiple choice questions and other pedagogically arranged questions are also provided to help students assess their subject knowledge. This book is designed primarily as a textbook for undergraduate and postgraduate students. It is also useful for undergraduate students of engineering.


5. “An Introduction to Probability and Statistics” by Vijay K Rohatgi and A K Md Ehsanes Saleh
“An Introduction to Probability and Statistics” Book Review: This book provides solutions as well as sufficient exercises for the readers desiring to gain maximum knowledge after the completion of the book. Provided in the book are chapters on basic concepts of Probability, Statistics and Random Variable etc. Other important topics covered in the book include theory of error functions, conditional probability, binomial distribution etc. Plethora of solved examples are included in every chapter of the book. Students pursuing BA and B. Com courses (Pass and Honours) as well as post graduate students of Arts and Commerce can benefit from the book. Students preparing for various competitive examinations may also find it beneficial.


6. “Probability and Statistics (Schaum’s Outline Series)” by Murray Spiegel and John Schiller
“Probability and Statistics (Schaum’s Outline Series)” Book Review: This book is the guideline for the statistics and probability courses provided all over the country. This book contains solved problems and examples for students to learn easily. Practising the exercises will sharpen the problemsolving skills of students. Get an outline of the course information and practice the exercises to test your skills. This course is generally offered to students at the first to third graduate college year, preferably after elementary courses. It has also been revised from timetotime to contain all the relevant changes happening each year. Chapters like introduction to basic probability theory and statistical inference, with a unique balance of theory and methodology are also provided in the subsequent chapters of the book. The topics in this book include binomial distribution, normal distribution, conditional probability, variance analysis and many more. This book highlights all the important facts you need to take note of. It helps to shorten your study time to get the best scores.


7. “Probability and Statistics for Engineers and Scientists” by Walpole
“Probability and Statistics for Engineers and Scientists” Book Review: This book is presented as a combination of analytical rigour as well as accessibility. New chapters such as histogram, hypothesis, covariance, independent events, mean, median etc have been added to the existing edition of the book. Also provided in the book are a plethora of examples as well as exercise questions to practice as well as test the concepts grasped by the book. It also has an allround introduction to basic concepts of Probability, Statistics and Random Variable with an excellent list of references and diagrams are also clearly labelled in the book. Students preparing for various competitive examinations as well as undergraduate students may find it fruitful.


8. “Probability – Statistics and Random Processes” by Veerarajan
“Probability – Statistics and Random Processes” Book Review: This book provides a clear explanation on the topics like introduction to basic probability theory and statistical inference, with a unique balance of theory and methodology in the book. This book is targeted for undergraduate engineering students enrolled in the course. Other important chapters contained in the book include law of large numbers, independent events, normal distribution, scatter diagram etc.


9. “Probability and Statistics” by E Rukmangadachari
“Probability and Statistics” Book Review: This textbook deals with the basic concepts of Probability, Statistics and Random Variable so that the subject is perceived by the student as both a science and an art. The theories and explanations are supported by a large number of solved examples. Additional figures have also been added for the clarity and understanding of the book. Multiple choice questions and other pedagogically arranged questions are also provided to help students assess their subject knowledge. This book is designed primarily as a textbook for undergraduate and postgraduate students. It is also useful for undergraduate students of engineering.


10. “Probability and Statistics with Reliability, Queuing and Computer Science Applications” by Trivedi
“Probability and Statistics with Reliability, Queuing and Computer Science Applications” Book Review: The book presents the subject matter of statistics and probability in a lucid way. It covers the syllabus by almost all the universities. This book can be used by both undergraduate and graduate students and also the teachers alike. The end of the chapter exercises are provided under three categories namely descriptive, analytical and objective which will be highly useful to the readers to test their comprehension of the subject. The various processes of practical approach to methods of statistical modeling and data analysis are treated systematically and in a logical sequence. The methods of analysis and interpretation of introduction to basic probability theory and statistical inference, with a unique balance of theory and methodology are presented in an unambiguous manner and their design applications are demonstrated through well formulated worked out examples.


11. “Advances in Combinatorial Methods and Applications to Probability and Statistics” by N Balakrishnan  
5. Probability, Random Process and Statistical Inference
1. “Probabilities, Random Variables and Random Processes” by Peyton Peebles
“Probabilities, Random Variables and Random Processes” Book Review: The book is an updated and revised piece of work featuring the latest theory of probability, random variables, and random signal principles. Many practical applications of probability are mentioned in this book, in order to explain the probability concepts. The content of this book is supported by large amounts of exercises. It provides easytograb knowledge to the readers. The book will be suitable for the juniorsenior level course in electrical engineering.


2. “Probability, Random Variables and Stochastic Processes” by A Papoulis
“Probability, Random Variables and Stochastic Processes” Book Review: The book is an uptodate edition, reflecting fundamental principles and basic applications of probability, random variables, as well as stochastic processes. The chapters of this book broadly cover repeated trials, Bernoulli’s theorem, random variable, different probability distributions, statistics parameter estimation, Poisson processes, Markov chains and processes, and queueing theory. For better understanding of the readers, several examples are included in this text. The book will be beneficial for the senior or graduate level courses in probability. The students of mathematics, physics, and electrical engineering will find this text valuable.


3. “Probability, Random Processes and Estimation Theory for Engineers” by H Stark and J W Woods  
4. “Probability and Random Processes” by Geoffrey R Grimmett and David R Stirzaker
“Probability and Random Processes” Book Review: This book provides a rigorous introduction to the field of probability theory and discusses the random processes in detail. The book focuses on providing a fair introduction to probability theory. The chapters of this book are selfcontained, organized, and contain detailed description of major random processes. The book basically has 4 main aims which are providing the concepts of basic probability in a straightforward manner, random processes discussion with examples, covering many important topics and impart the beginner with advanced work. The topics like sampling, Markov chain, Monte Carlo, geometric probability, coupling, Poisson approximation, large deviations, spatial Poisson processes, renewalreward, queueing networks, and stochastic calculus are thoroughly explained. Many exercises and problems are included in text for selfstudy and selfassessment for the readers. The book can be referred for the undergraduate courses in mathematics, statistics and the sciences.


5. “Probability and Random Processes for Electrical Engineering” by Albert LeonGarcia
“Probability and Random Processes for Electrical Engineering” Book Review: The book reflects a proper introduction of probability and random processes. The chapters of this book are comprehensive and precise. The book describes the suitable processes and methods for transition of real problems to probability models for those problems. It enables the readers in brushing up their problemsolving skills. For providing relatable content to the readers, many practical applications of probability theory in electrical and computer engineering are highlighted. The book also features discretetime random processes for portraying the relationship between random variables and continuoustime random processes. A section of this book is devoted to random processes.


6. Probabilistic Models
1. “Introduction to Probability Models” by Sheldon M Ross
Book Review: This book provides introduction to probability theory and stochastic processes. The book also deals with the heuristic and nonrigorous concepts of probability and probability using the tools of measure theory. The book demonstrates the basics of probability like random variable, conditional probability and conditional expectation. The book also discusses stochastic processes, poison processes and markov chains. The book also contains chapters on queuing, reliability theory and simulation. The book is useful for students studying probability in the field of engineering, computer science, management and operations research.


2. “Introduction to Probability Models: Operations Research” by Wayne L Winston
Book Review: This book covers various probability models with contributions from financial engineering, computational simulation and manufacturing engineering. The book lays more emphasis to probability models along with the addition of practical breakthroughs thereby becoming the first book to introduce various ideas at an accessible level. The book also contains numerous problems. The book is known for the balance that it offers by illustrating the theoretical concepts along with many examples. The book also contains many exercises that widely cover probability topics.


3. “Introduction to Probability” by Dimitri P Bertsekas and John N Tsitsiklis
Book Review: This book provides introduction to probability theory, stochastic processes and probabilistic models that are used in the field of science, engineering, economics and many other related fields. This is a very good probability textbook for graduate and undergraduate students. The book also contains fundamentals of probability theory and advanced topics like transforms, sums of random variables, least square estimation, bivariate normal distribution, Bernoulli, poisson and markov processes and many more. The book also contains numerous solved theoretical problems.


3. “Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms” by Dechter
“Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms” Book Review: The book covers introduction to graphical models, exact algorithms for reasoning with such models and all the important principles of models. The topics like inferencebased, messagepassing schemes, searchbased conditioning schemes, bucket elimination for probabilistic networks, treeclustering schemes, and/or search spaces, algorithms for graphical models, combining search, trading space for time, and bucket elimination for deterministic networks are described in it. The book will be useful for researchers and students in the artificial intelligence and machine learning area, and beyond.


4. “Probabilistic Graphical Models” by Van Der Gaag
“Probabilistic Graphical Models” Book Review: The book covers each and every characteristic of graphical models for probabilistic reasoning, decision making, and learning. It consists of thirtyeight revised full papers explaining the above topics. The content of this book is inspired from the 7th International Workshop on Probabilistic Graphical Models held in the Netherlands, in September 2014.


5. “Probabilistic Models for Nonlinear Partial Differential Equations” by Carl Graham
“Probabilistic Models for Nonlinear Partial Differential Equations” Book review: The book describes weak convergence of stochastic integrals, the probabilistic interpretation, the particle approximation of equations, the modelling of networks by interacting particle systems in detail. Some basic laws and principles of physics like conservation laws, Boltzmannlike, and NavierStokes equations are used as tools in this text. The book will be useful for the PhD students, young researchers, and probabilists working on stochastic particle methods and on the approximation of SPDEs.


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