We have compiled the list of Best Reference Books on Statistics subject. These books are used by students of top universities, institutes and colleges. Here is the full list of best books on Statistics along with reviews.
Kindly note that we have put a lot of effort into researching the best books on Statistics 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 “Statistics” 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 Statistics Books with author’s names, publishers, and an unbiased review as well as links to the Amazon website to directly purchase these books.
 Engineering Statistics
 Probability and Statistics
 Introduction to Mathematical Statistics
 Nonparametric Statistics
 Statistical Methods
 Statistical Methods of Analysis and Design
 Statistical Inference
 Statistical Modeling
 Applied Statistics
 Applied Statistics and Mathematical Statistics
1. Engineering Statistics
1. “Engineering Statistics” by Douglas C Montgomery
“Engineering Statistics” Book Review: The book is a modern presentation of engineering statistics. It explains the use of statistical tools into the engineering problemsolving process. The book consists of topics like descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and statistical process control. This text contains many examples and exercises for better understanding and self assessment of the readers.


2. “Mathematical Statistics with Applications” by Dennis Wackerly
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Book Review: This book presents a strong foundation in the field of statistical theory thereby covering the importance of theory in solving many real world problems. The book makes use of many practical applications and contains numerous exercises that deal with the nature of statistics and determines its role in scientific research. The book contains chapters on graphical methods, numerical methods, probability and interference, binomial and geometric probability distribution, normal, gamma, beta and multivariate probability distributions and many more.


3. “Mathematical Statistics and Data Analysis” by John A Rice
Book Review: This book deals with the mathematical statistics course. The book contains numerous topics along with data analysis and practices most of the concepts of statistics with the help of computer. The author basically focuses on the data analysis, examines real problems with real data and encourages theoretical concepts. The book also contains statistical information, graphical displays and many realistic applications.


4. “Statistical Inference” by Roger Berger and George Casella
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Book Review: This book demonstrates the building of theory of statistics with the help of first principles of probability theory. The author makes use of techniques, definitions and statistical concepts in order to develop statistical inference theory. This book is very useful at the graduate level and is useful for students studying statistics and who have a strong mathematical background. The book also stresses on the practical usage of statistical concepts along with the understanding of basic statistical concepts. Topics like various types of discrete, continuous distribution with solid proofs are taken up in detail. Example problems are provided for to get an indepth understanding. Advanced topics like random number generation, simulation methods, bootstrapping, EM algorithm, pvalues and robustness are covered. This book is suitable for firstyear graduate students in statistics.


5. “Springer Handbook of Engineering Statistics” by Pham Hoang
“Springer Handbook of Engineering Statistics” Book Review: This book will be helpful for the engineers, statisticians, researchers, teachers, and students of all fields. The book presents many statistical techniques so that the readers can gain sensible statistical feedback. The book features topics like fundamental statistics process monitoring and improvement, reliability modeling and survival analysis, regression methods, data mining, statistical methods and modeling, and a wide range of applications including six sigma. The book provides the reader sufficient knowledge about the products and how their products can be improved.


6. “Modern Engineering Statistics” by Thomas P Ryan
“Modern Engineering Statistics” Book Review: The book gives a statistical approach to engineering applications. It maintains an excellent balance between methodology and applications of engineering statistics. The book explains basic concepts before moving to complex statistical techniques. Each chapter is ended with its summary. The book consists of many examples, exercises, case studies and illustrations. It gives a clear explanation about the relationship between hypothesis tests and confidence intervals. Tools like ‘Minitab’ and ‘JMP’ are used to illustrate statistical analyses.


7. “Modern Statistical and Mathematical Methods in Reliability” by Wilson Alyson
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“Modern Statistical and Mathematical Methods in Reliability” Book Review: The book is based on ‘Reliability Theory’. All the research activities and applications of reliability theory are mentioned in this book. It consists of topics like reliability modeling, network and system reliability, Bayesian methods, survival analysis, degradation and maintenance modeling, and software reliability. The book is inspired from the papers presented at The Fourth International Conference on Mathematical Methods in Reliability in Santa Fe, New Mexico.


8. “Computational Methods for Reliability and Risk Analysis” by Enrico Zio  
9. “Lifetime Data: Statistical Models and Methods” by Jayant V Deshpande
“Lifetime Data: Statistical Models and Methods” Book Review: The book is basically for students, post graduating in statistics, engineering statistics and medical statistics courses. The concept and role of ageing in choosing appropriate models for lifetime data is discussed in detail. It consists of topics like ageing, tests for exponentiality, competing risks and repairable systems. The book features ‘Public Domain Rsoftware’. Working and use of the preceding software is clearly explained in this book.


10. “Paperback : Si Version ENGINEERING STATISTICS” by Runger
“Paperback: Si Version Engineering Statistics” Book Review: The book gives updated information about engineering statistics. It gives an explanation about integration of statistical tools in the process of problem solving in engineering. All the major topics related to engineering statistics like descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and statistical process control are discussed in detail.
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11. “Statistics for Everyone: A Spreadsheet Oriented Approach” by Dr. A N Sah  
12. “All of Statistics: A Concise Course in Statistical Inference” by Larry Wasserman
“All of Statistics: A Concise Course in Statistical Inference” Book Review: The book aims at presenting a detailed theory on all the major aspects of statistics. The chapters of this are fully updated and feature many stateoftheart topics like nonparametric curve estimation, bootstrapping, and classification. The process of analyzing the data is also addressed in this text. Basic calculus and linear algebra are used as tools in some of the featured topics and methods. The book will be an asset for the graduating and advanced undergraduating students of computer science, mathematics, and statistics. It will be equally important for the students and researchers of data mining and machine learning.


13. “Introductory Statistics” by Prem S Mann
“Introductory Statistics” Book Review: The book is an updated and revised piece of writing featuring latest topics, methods, and applications in the field of statistics. The topics featured in this book are inspired from a wide range of disciplines and media sources. The chapters of this book contain marginal notes, stepbystep solutions, and several examples. It is a rich source of information illustrated with several realworld problems and solutions. The applications of featured concepts and methods are clearly explained with the help of case studies and examples. The book will be an asset for the business professionals.


2. 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 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.


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 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.


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.


3. Introduction to Mathematical Statistics
1. “Statistical Inference” by G Casella and B L Berger
“Statistical Inference” Book Review: The book is written from both theoretical as well as practical point of view. The topics like ancillarity, invariance, Bayesian methods, pivots, Stein estimation, errors in variables, and inequalities are discussed in detail. The book highlights practical uses of statistical theory. It enables the readers in deriving reasonable statistical procedures for dealing with different situations and problems. The recent developments in the field of statistics are enlisted in this text. The book will be useful for students and professionals of mathematics.


2. “Probability and Statistics” by M H DeGroot
“Probability and Statistics” Book Review: The book reflects major aspects and applications of probability and statistics. It also features basic calculus and elementary properties of vectors and matrices. The chapters of this book cover classical and Bayesian methods, simulation, Markov chain, Monte Carlo, Bootstrap, and residual analysis in linear models. For better understanding of the readers, the book consists of several examples. The book will be beneficial for the students dealing with mathematics, probability, and statistics.


3. “Theory of Point Estimation” by E L Lehmann and G Casella
“Theory of Point Estimation” Book Review: The book is an updated and revised piece of work featuring contemporary topics and recent developments in point estimations. The chapters of this book cover all the major topics related to preparations, unbiasedness, equivariance, average risk optimality, minimaxity, admissibility, and asymptotic optimality. Many problems and examples are included in this text for selfstudy and practice of the readers. The Bayesian and hierarchical Bayesian approaches along with simultaneous estimation are discussed in detail. The book also reflects the suggestions and scopes for further study.


4. “Introduction to Mathematical Statistics” by Robert V Hogg  
5. “Introduction to Mathematical Statistics and Its Applications” by Richard J Larsen and Morris L Marx
“Introduction to Mathematical Statistics and Its Applications” Book Review: The book is a wellstructured and selfcontained text, featuring theoretical aspects of mathematical statistics. The initial section of the book describes topics like probability, random variables, special distribution, estimation, hypothesis testing, and normal distribution. Moving on, types of data, twosample interferences, goodnessoffit tests, regression, analysis of variance, randomized block design, and nonparametric statistics are thoroughly explained. Each chapter consists of several examples. The book highlights the application of statistical methods while reinforcing calculus. To give better practical knowledge and relatable content to the readers realworld data and many case studies are included in this book.


6. “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: The book presents a thorough review on the field of statistical learning. It reflects many essential modeling and prediction techniques along with relevant applications. The topics like linear regression, classification, resampling methods, shrinkage approaches, treebased methods, support vector machines, and clustering are thoroughly explained. The applications, implementation, and uses of the featured methods and techniques are described in a readerfriendly manner. To give the book’s content visual support illustrations, color graphics and realworld examples are included. The book will be suitable for the practitioners in fields of science and industry. The statisticians and nonstatisticians seeking deep knowledge in statistical learning techniques will find this text helpful.


7. “Introduction to Mathematical Statistics” by Paul G Hoel
“Introduction to Mathematical Statistics” Book Review: The book is an excellent blend of both theoretical aspects and applications of statistics. The chapters of this book cover all the major topics related to probability, probability distributions, sampling theory, correlation and regression, statistical inference, testing goodness of fit, small sample distributions, and statistical design. Many methods underlying statistics namely, nonparametric methods, empirical methods, and statistical methods are introduced in this text. For better illustration of featured concepts several problem sets are mentioned throughout the book.


8. “Statistical Inference” by George Casella
“Statistical Inference” Book Review: The book aims at presenting fundamental statistical concepts for deriving reasonable statistical procedures in order to deal with a variety of situations. The chapters of this book are based on random number generation, simulation methods, bootstrapping, EM algorithm, and pvalues. The advanced topics like logistic regression and robust regression are explained efficiently. The practical uses and applications of statistical theory are clearly mentioned in this book. The development of statistical inference using techniques, definitions, and concepts is addressed in this text. The content of this book is clearly illustrated with the help of examples. The book will be a good resource for firstyear graduate students majoring in statistics.


9. “Introduction to the Practice of Statistics” by David S Moore and George P McCabe
“Introduction to the Practice of Statistics” Book Review: The book is a fully updated and revised edition reflecting latest topics and recent research in statistics. The chapters of this book are quite efficient and describe each topic and concept in proper steps. The book stresses on data analysis and critical thinking. The applications of statistics in various professions and fields are highlighted in this text. It also lays an emphasis on the use of computers and calculators for problem solving. The book will be an ideal resource for students of mathematics as well as statisticians.


10. “Introduction to Probability and Mathematical Statistics” by Lee J Bain and Max Engelhardt
“Introduction to Probability and Mathematical Statistics” Book Review: The book presents a wellstructured theoretical introduction to probability and mathematical statistics. The chapters of this book are selfcontained and feature all the essential topics and major aspects of probability as well as mathematical statistics. For better understanding of the readers, many realistic exercises and examples are featured in this book. The topics like sampling distributions, sequential tests, regression, and linear models are discussed in detail. The book will be valuable for students of mathematics as well as the individuals interested in probability and statistics.


4. Nonparametric Statistics
1. “Applied Nonparametric Statistics” by W W Daniel
“Applied Nonparametric Statistics” Book Review: This book is for students in the Mathematics area. This book contains ten chapters with appendices at the end. The book begins with an introduction on Hypothesis testing, nonparametric statistics and format and organization. This book contains information on procedures for utilizing data from a single sample. Discussion on different numbers of independent and related samples is also given in this book. This book gives a description on ChiSquare test and goodnessoffit test and their mathematical properties. This book also provides details of rank correlation and their association measures and simple linear regression analysis. Each chapter contains review exercises and references which is helpful for the understanding of concepts.


2. “Nonparametric Statistical Inference” by M Hollandor
“Nonparametric Statistical Inference” Book Review: This book is for upperlevel undergraduate or firstyear graduate students. This book provides detailed description on nonparametric regression methods and the bootstrap. A detailed explanation on contingency tables and the odds ratio and life distributions and survival analysis is given in this book. Topics like nonparametric methods for experimental designs and some more procedures, realworld data sets, and problems have been given in depth in this book. This book contains illustrated examples that use Minitab and StatXact. This book also contains detailed solutions to all the problems which is helpful in understanding.


3. “Nonparametric Statistical Methods Based on Ranks” by E L Lehmann
“Nonparametric Statistical Methods Based on Ranks” Book Review: This book is for graduate students. This book gives an introduction to nonparametric methods for the analysis and planning of comparative studies. This book gives an indepth discussion on Rank tests. This book gives a thorough description of these tests and their estimating procedures. Each chapter ends with mathematics and many exercises. This book also gives illustrative examples which is useful for understanding purposes.


4. “Textbook of Parametric and Nonparametric Statistics” by Vimala Veeraraghavan and Suhas Shetgovekar
“Textbook of Parametric and Nonparametric Statistics” Book Review: This book is for students and researchers of social sciences. This book contains methods of parametric and nonparametric statistics. An indepth on correlation and regression, analysis of variance, and test construction are provided in this book. This book gives detailed information on SPSS and Excelbased statistical analysis of data. This book also gives discussion on use of statistics in psychology and psychological test construction. This book contains worked out examples which are for understanding purposes.


5. “Nonparametric Statistics for Stochastic Processes: Estimation and Prediction (Lecture Notes in Statistics)” by D Bosq
“Nonparametric Statistics for Stochastic Processes: Estimation and Prediction (Lecture Notes in Statistics)” Book Review: This book is for specialists in Mathematics statistics. This book provides discussion on the theory of nonparametric estimation and prediction for stochastic processes. Topics like discrete time and continuous time have been discussed in detail in this book. Kernel methods have also been discussed in very detail. This book gives an explained discussion on optimal and super optimal convergence rates. This book contains examples which helps in understanding concepts more clearly.


6. “Nonparametric Statistics for Behavioural Science” by Sidney Siegel and Castellan  
7. “The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics (Oxford Handbooks)” by Jeffrey Racine and Liangjun Su
“The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics (Oxford Handbooks)” Book Review: This book is for researchers in the field of Statistics. This book contains chapters by various famous international econometricians and statisticians. This book contains detailed information on statistical methods for nonparametric and semiparametric procedures. The modeling of crosssection, time series, panel, and spatial data have been discussed in detail in this book. Topics like methodology of semiparametric models and special regressor methods have been explained in the book. This book also contains an indepth on true error of competing approximate models, support vector machines and their modeling of default probability. This book discusses some new approaches to the analysis of nonparametric models with exogenous treatment assignment.


8. “Nonparametric Statistics (The Six Sigma Research Institute Series)” by David C Sutor and Donald B White  
9. “All of Nonparametric Statistics: A Concise Course in Nonparametric Statistical Inference (Springer Texts in Statistics)” by Larry Wasserman
“All of Nonparametric Statistics: A Concise Course in Nonparametric Statistical Inference (Springer Texts in Statistics)” Book Review: This book is for Master’s level and Ph.D. level students. This book gives a detailed description on nonparametric delta method and nonparametric regression. This book provides an explanation on minimax estimation and density estimation. Topics like nonparametric confidence sets, and wavelets have been covered in detail. This book gives discussion on orthogonal function methods and bootstrap.This book contains theory and methodology which is helpful for understanding purposes.


10. “Nonparametric Statistics for Behavioural Science (Psychology)” by Sidney Siegel  
5. Statistical Methods
1. “Statistical Methods (Combined Volume)” by Das N
“Statistical Methods (Combined Volume)” Book Review: This book is designed for the students of biomedical engineering, researchers and scientists. It basically deals with the statistical methods. It also covers the formulas, results, theorems and proofs of statistical methods. It consists of solved examples, exercises and short questions at the end of the chapter.


2. “Statistical Methods” by S P Gupta
“Statistical Methods” Book Review: This book is designed for the students, researchers and scientists. It explains the use of statistical methods in various fields like biological, demographic, economic, health and physical. It discusses the applications and statistical methods. This book is divided into two parts. The first part covers the statistical methodology. And the second part covers the complex approaches of statistical data analysis. It consists of solved examples, exercises and short questions at the end of the chapter.


3. “Statistical Methods: An Introductory Text” by J Medhi
“Statistical Methods: An Introductory Text” Book Review: This book is designed for the students, researchers and scientists. It focuses on the understanding and application of statistical methods. It covers the theorems, results and proofs of statistical method. It also discusses the statistical inference and tests of significance. It consists of solved examples, exercises and short questions at the end of the chapter.


4. “Statistical Methods: Concepts, Application and Computation” by Y P Aggarwal
“Statistical Methods: Concepts, Application and Computation” Book Review: This book is designed for the students, researchers and scientists. It basically deals with the concepts, applications and procedures involved in statistical analysis. It explains the information of multivariate analysis. It covers the parametric and non parametric tests. It focuses on the assumptions of homogeneity and normality. It consists of solved examples, exercises and short questions at the end of the chapter.


5. “Statistical Methods for Engineering and Sciences” by Asad U Khan
“Statistical Methods for Engineering and Sciences” Book Review: This book is designed for engineering students, mathematicians, researchers and scientists. It is divided into 12 chapters. It basically deals with the statistical methods. It provides the applications of the statistical methods. It also consists of the solved examples, exercises and short questions at the end of the chapter.


6. “Statistical Methods in Geographical Studies: Student Edition” by Aslam Mahmood
“Statistical Methods in Geographical Studies: Student Edition” Book Review: This book is designed for the geographers, researchers and social scientists. It basically deals with the graphical representation of the data, theory of correlation and network analysis. The topics which are discussed are regression near neighbour analysis, rank size rule, gravity and potential model. It also focuses on the principal component analysis and discriminant analysis. It consists of solved examples, exercises and short questions at the end of the chapter.


7. “Statistical Methods for Quality Improvement” by Hitoshi Kume
“Statistical Methods for Quality Improvement” Book Review: This book is designed for the students, researchers and social scientists. It explains the methods of statistics to real world problems. It focuses on the concepts, principles and techniques of statistical methods. It discusses the understanding of the production process. It consists of solved examples, exercises and short questions at the end of the chapter.


8. “Statistical Methods for Research” by K Kalyanaraman
“Statistical Methods for Research” Book Review: This book is designed for the students, researchers and scientists. It provides the concepts of various statistical tools and its applications. It also explains the concepts with the help of diagrams and figures. The topics are statistical reasoning, probability and sampling. It discusses the twovariable analysiscorrelation and regression. It consists of solved examples, exercises and short questions at the end of the chapter.


9. “Biostatistics a Manual of Statistical Methods for Use in Health, Nutrition and Anthropology” by Rao
“Biostatistics a Manual of Statistical Methods for Use in Health, Nutrition and Anthropology” Book Review: This book is designed for the researchers, students, chemists and scientists. It is divided into 9 sections. It basically covers the statistical data and analysis in medicine, health and nutrition. It provides the concepts and applications of the statistical methods. The topics which are covered in this book are biostatistics, analysis of covariance and analysis of variance. It consists of solved examples, exercises and short questions at the end of the chapter.


10. “An Introduction to Statistical Methods” by C B Gupta
“An Introduction to Statistical Methods” Book Review: This book is designed for the researchers, students, chemists and scientists. It basically discusses the application of statistical methods in commerce, business and other social sciences. It also explains the theory of games. It provides the information of various statistical techniques and also explains its use. It focuses on the significance of various statistical concepts. It consists of solved examples, exercises and short questions at the end of the chapter.


6. Statistical Methods of Analysis and Design
1. “Engineering Statistics” by A B Bowker and G J Liberman  
2. “Statistics and Experimental Design in Engineering and the Physical Sciences” by N L Johnson and F C Xeen Leone  
3. “Probability and Statistical Inference” by R V Hogg and E A Tanis
“Probability and Statistical Inference” Book Review: This applied introduction to the mathematics of probability and statistics concentrate on the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. This book has a studentfriendly approach along with a solid organisation of knowledge and has a balanced coverage of the topic. The book is divided into eleven topics they are Probability, Discrete Distributions, Continuous Distributions, Bivariate Distributions, Distributions of Functions of Random Variables, Estimation, Tests of Statistical Hypotheses, Nonparametric Methods, Bayesian Methods, Some Theory, Quality Improvement Through Statistical Methods along with some references and exercises.


4. “The Design and Statistical Analysis of Animal Experiments” by Dr Simon T Bate and Dr Robin A Clark
“The Design and Statistical Analysis of Animal Experiments” Book Review: his book is a comprehensive guide to the design and statistical analysis of animal experiments. This book explains the statistical tools employed by practitioners by making real life experiments. This book includes a range of design types they are block, factorial, nested, crossover, doseescalation and repeated measures so as to analyse the data generated experimentally. The book is simple and describes in nonmathematical terms, helping readers without a statistical background to understand key techniques. This book includes topics like Statistical concepts, Experimental design, Randomisation, Statistical analysis, Analysis using In VivoStat along with some references and index.


5. “Design of Experiments: Statistical Principles of Research Design and Analysis” by Robert
“Design of Experiments: Statistical Principles of Research Design and Analysis” Book Review: This book provides an overall view of the subject and provides a realistic setting as possible for conducting an actual research project. This book includes all design strategies and emphasizes hypotheses related to treatment design. This book has real world examples which are actually based on research studies. This book makes us know not why to apply but how to apply the theories along with identifying a treatment design that addresses the problem. This book has numerous examples which are based on actual studies & real data. This book is divided into 17 chapters they are. Research Design Principles, Getting Started with Completely Randomized Designs, Treatment Comparisons, Diagnosing Agreement Between the Data and the Model, Experiments to Study Variances, Factorial Treatment Designs, Factorial Treatment Designs: Random and Mixed Models, Complete Block Designs, Incomplete Block Designs: An Introduction, Resolvable and Cyclic Designs, Factorial Treatment Designs, Fractional Factorial Designs, Response Surface Designs, SplitPlot Designs, Repeated Measures Designs, Crossover Designs, Analysis of Covariance.


6. “Propensity Score Analysis: Statistical Methods and Applications” by Shenyang Guo and Mark W Fraser
“Propensity Score Analysis: Statistical Methods and Applications” Book Review: This book covers the subject in a systematic manner with review of the origins, history, and statistical foundations and illustrates how to use methods for solving evaluation problems. This book focuses on practical applications of various types of data and evaluation problems, strategies for using the methods along with covering the limitations. This book covers topics like Counterfactual Framework and Assumptions, Conventional Methods for Data Balancing, Sample Selection and Related Models, Propensity Score Matching and Related Models, Propensity Score Subclassification, Propensity Score Weighting, Matching Estimators, Propensity Score Analysis With Nonparametric Regression, Propensity Score Analysis of Categorical or Continuous Treatments: Dosage Analyses, Selection Bias and Sensitivity Analysis, etc along with some remarks and Examples.


7. “An Introduction to Statistical Methods and Data Analysis” by R Lyman Ott and Micheal T Longnecker
“An Introduction to Statistical Methods and Data Analysis” Book Review: This book covers the topic very well and provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior coursework in statistics. This book helps the reader to be critical to the subject and to make decisions based on data and solving real world problems. This book covers topics such as Statistics, Using Surveys and Scientific Studies to Gather Data, Data Description, Probability and Probability Distributions, Inferences about Population Central Values, Inferences Comparing Two Population Central Values, Inferences about Population Variances, Inferences about More Than Two Population Central Values. It also covers some advanced topics like Multiple Comparisons, Categorical Data, Linear Regression and Correlation, Multiple Regression and the General Linear Model, More on Multiple Regression, Design Concepts for Experiments and Studies, Analysis of Variance for Standard Designs, Communicating and Documenting the Results of Analyses, etc in detail.


8. “Statistical Methods for Psychology” by David C Howell
“Statistical Methods for Psychology” Book Review: This book is resourceful and easy to understand and has the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. This book emphasizes conceptual understanding so that students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text.This book focuses on two things first is the importance of looking at the data before beginning a hypothesis test, and the second is the importance of knowing the relationship between the statistical test in use. This book is divided into sub topics and they are Describing and Exploring Data, The Normal Distribution, Sampling Distributions and Hypothesis Testing, Basic Concepts of Probability, Categorical Data and ChiSquare, Hypothesis Tests Applied to Means, Power, Correlation and Regression, Alternative Correlational Techniques, Simple Analysis of Variance, Multiple Comparisons Among Treatment Means, Multiple Comparisons Among Treatment Means, RepeatedMeasures Designs, Multiple Regression, Analyses Of Variance and Covariance as General Linear Models, MetaAnalysis and SingleCase Designs, etc.


9. “Factor Analysis: Statistical Methods and Practical Issues” by JaeOn Kim and Charles W Mueller
“Factor Analysis: Statistical Methods and Practical Issues” Book Review: This book covers the topic well and focuses on exploratory factor analysis, confirmatory factor analysis and various methods of constructing factor scales. This book covers the topics like The conceptual foundation of factor analysis, Methods of Extracting Initial Factors, Methods of Rotation, Number of Factors Problem Revisited, Introduction to Confirmatory Factor Analysis, Construction of Factor Scales are also explained with examples. The book describes initial factoring and factor rotation in detail.


10. “The Statistical Analysis of Experimental Data” by John Mandel
“The Statistical Analysis of Experimental Data” Book Review: This book offers precise measurements with numerous problems. The book here draws a clear and fascinating blueprint for a systematic science of statistical analysis. This book approaches with examples aimed specifically at statistical problems. This book comprises a thorough grounding in the fundamental mathematical definitions, concepts, and facts underlying modern statistical theory. The book determines the most effective methodology using statistics as an interpretative tool. This book also includes many examples which are worked step by step and helpful figures and tables with summary of the chapters, the chapters are The Nature of Measurement, Statistical Models and Statistical Analysis, The Mathematical Framework of Statistics Part, The Mathematical Framework of Statistics Part, Homogeneous Sets of Measurements, The Precision and Accuracy of Measurements, The Method of Least Squares, Testing the Statistical Model, The Analysis of Structured Data, Some Principles of Sampling, The Fitting of Curves and Surfaces, The Fitting of Straight Lines, etc.


7. Statistical Inference
1. “Statistical Inference” by Rajagopalan
“Statistical Inference” Book Review: This book starts with the basics of probability. Topics like first principles of probability theory, the theory of statistical inference, techniques, consequences are covered elaborately. This book has a neat presentation. This book focuses on practical uses of statistical theory. This book serves as a useful reference material for pg students as well as to statisticians. The author suggests having a solid mathematical background before reading this book.


2. “Statistical Inference: Theory of Estimation” by Kumar S M
“Statistical Inference: Theory of Estimation” Book Review: The book commences with describing growing levels of data summarization, minimal sufficient statistics, Blackwell theorem and a lot more. Students can review their understanding of the concepts using the chapterend exercise questions. Advanced topics like CramerRao, Bhattacharyya variance lower bounds, Robbins and Kiefer variance lower bounds for Pitman models are discussed elaborately. Solved examples are provided to understand the concepts deeply. Separate chapters are dedicated to essential topics like Pitman estimator, Empirical Bayes, scale models, and a few more. This book is suitable for PG students of statistics streams.


3. “Statistical Inference” by Kumar and Chaudhary  
4. “Linear Statistical Inference and its Application” by C Radhakrishna Rao  
5. “Statistical Inference: Testing of Hypotheses” by Srivastava
“Statistical Inference: Testing of Hypotheses” Book Review: This book focuses on J. Neyman and Egon Pearson’s mathematical foundations of hypothesis testing. This book is written in a studentfriendly way. Topics like optimality, asymptotic relative efficiency, consistency, and asymptotic null distribution are explained in a clearcut manner. Dedicated chapters are provided for essential topics like testing of hypothesis, ratio tests, and few more. This book serves as a ready reference for the researchers in the areas of biostatistics and econometrics.


6. “Probability and Statistical Inference” by HOGG
“Probability and Statistical Inference” Book Review: This book starts by covering basic concepts of probability like enumeration techniques, and Baye’s Theorem. The examples help us to understand the concepts more deeply. Topics like discrete probability distributions, continuous probability distributions, multivariate distributions, the Normal Distribution and many more are taken up in detail. Practice exercises are given to check our understanding of the concepts. The books end with providing a brief introduction to set theory, limits, infinite series, integration, and multivariate calculus.


8. Statistical Modeling
1. “Density Estimation for Statistics and Data Analysis” by B W Silverman
“Density Estimation for Statistics and Data Analysis” Book Review: This book describes the methods of density estimation for statistics and data analysis. Main topics in road are survey of existing methods, the kernel method for univariate data, Kernel method for multivariate data. Other topics included are 3 important methods, density estimation in action. around 50 graphs and figures are provided throughout the book for easy understanding of the important techniques. This book is helpful for computational engineers and statistical mathematics students.


2. “Tools for Statistical Inference” by M. A. Tanner
“Tools for Statistical Inference” Book Review: This book discusses the tools required for data augmentation methods and for statistical inference. Remain topics mentioned are normal approximation to likelihoods and to posterior, The EM algorithm, the data augmentation algorithm. Another topic mentioned is the Markov chain Monte Carlo algorithm. Open examples are provided for each algorithm with code. This book is beneficial for data analysis students and statistical mathematics students.


3. “An Introduction to the Bootstrap” by B Efron and R J Tibshirani
“An Introduction to the Bootstrap” Book Review: This book provides an introduction to the bootstrap. it provides computational techniques to analyse and understand the difficult data sets. Main topics mentioned are the accuracy of a sample mean, Random samples and probabilities, the empirical distribution function and the plugin principle. Other topics included are standard errors and estimated standard errors, the bootstrap estimate of standard errors, regression models. End of chapter problems are introduced for students to get the most out of the chapters. Bibliographic notes are added at the end of each chapter. This book is useful for engineers and statisticians who are in the field of data analysis.


4. “Statistical Digital Signal Processing and Modeling” by Monson H Hayes
“Statistical Digital Signal Processing and Modeling” Book Review: This book describes the important and advanced topics on digital signal processing and modelling. Topics mentioned are discrete time random processes, signal modelling, the levinson recursion, lattice filters. Other topics included are Wiener filtering, spectrum estimation, adaptive filtering, recursive least squares. Problems and their respective solutions are discussed at the end of each chapter. MATLAB programs and tables of symbols are added at the end of the book. This book is beneficial for statisticians and engineers in the field of electronics and communication.


5. “Modeling and Simulation Using MATLAB – Simulink: For ECE” by Dr Shailendra Jain
“Modeling and Simulation Using MATLAB – Simulink: For ECE” Book Review: This book mentions the modelling and simulation using the matlab software. Main topics discussed are introduction to matlab, matlab basics, programming in matlab, basic electrical and networks applications. Other topics mentioned are introduction to Simulink, fuzzy logic and applications, artificial neural network applications. All the text is supported by proper codes added in this book. This book is beneficial for electronics and electrical engineering students.


6. “Applied Predictive Modeling” by Max Kuhn and Kjell Johnson
“Applied Predictive Modeling” Book Review: This book covers the techniques used in predictive Modeling. Main topics mentioned are data preprocessing, overfitting and model tuning, regression models, measuring performance in regression models. Other topics in today car nonlinear regression models, regression trees and rulebased models, classification models, measuring predictor importance. exercises are added at the end of each chapter for students to practice. case studies are added in the end of some chapters to provide students some practical knowledge. This book is beneficial for advanced mathematical students and engineers working in the data processing and data analysis field.


7. “Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering” by Dimitris G Manolakis and Vinay K Ingle
“Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering” Book Review: This book provides the information regarding signal processing with statistical and adaptive approach. Main topics included are treatment of spectral estimation, signal model, adaptive filtering and array processing. Around 300 illustrations and over 3000 equations are provided in this book for students’ easy learning. References also includes matlab functions which are solved on all realworld problems. Students studying electronics and electrical engineering, mathematicians can refer to this book.


8. “Statistical Rethinking: A Bayesian Course with Examples in R and Stan” by Richard McElreath
“Statistical Rethinking: A Bayesian Course with Examples in R and Stan” Book Review: This book explains The Bayesian Inference with examples in R and Stan programs. Main topics included are the golem of Prague, Small worlds and large worlds, sampling the imaginary, geometric methods. Other chapters such as the many variables and the spurious waffles, the haunted DG and the casual terror are also discussed. a practice section is also added at the end of each unit 4 testing the knowledge of students and practicing purposes. Complete R code examples are also provided in this book. This book is designed for PhD students and experienced professionals in the field of specialized statistical modelling.


9. “Statistical Modeling and Computation” by Dirk P Kroese and Joshua C C Chan
“Statistical Modeling and Computation” Book Review: This book consists of topics regarding statistical modelling and computation. Main topics discussed are probability models, random variables and probability distribution, joint distribution. Other chapters included are statistical inference, common statistical models, likelihood, Monte Carlo sampling. Discussed at the end of each unit for student’s practice. Appendix consists of Matlab programs. This book is suitable for undergraduate students.


10. “Statistical and MachineLearning Data Mining: Techniques for Better Predictive Modeling and Analysis” by Bruce Ratner
“Statistical and MachineLearning Data Mining: Techniques for Better Predictive Modeling and Analysis” Book Review: This book covers the concept and techniques in statistical and machine learning data mining. Chapters included are science dealing with data, 2 basic data mining methods for variable assessment, CHAID based data mining for paired variable assessment. Other topics included are Symmetrising ranked data, the importance of straight data, principal component analysis, Market share estimation. a total of 43 chapters are discussed with different quantitative techniques in the field of data mining. in some of the chapters case studies are also mentioned. This book is useful for data mining and predictive modelling graduate students.


9. Applied Statistics
1. “Probability Concepts in Engineering Planning and Design” by Ang H S and Tang W H
Book Review: This book presents mathematical concepts and illustrates variety of engineering type problems and is a very suitable textbook for practicing engineers who require working knowledge of basic concepts and tools of probability. This book enables the students and engineers to learn probability as a part of their professional engineering background. One part of the book deals with basic concepts and methods of probability and statistics and the other part presents advanced concepts and applications including risk analysis, reliability analysis and probability based design.


2. “Probability Statistics and Decision for Civil Engineers” by Benjamin J R and Cornell C A
“Probability Statistics and Decision for Civil Engineers” Book Review: The book is an updated and revised piece of work featuring latest theory and recent developments in civil engineering. The book covers both theoretical as well as practical aspects of strength of materials, soil mechanics, construction planning, and water resource design. The book also includes concepts of statistics and probability. This book will be useful for students and professionals of civil engineering.


3. “Probability and Statistics for Engineers” by Little R E  
4. “Analysis and Adjustment of Survey Measurements” by Mikhail E M and Gracie G  
5. “Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control” by James Spall
“Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control” Book Review: The book covers both theoretical as well as practical aspects of stochastic algorithms. The book is a comprehensive piece of writing presenting all the concepts of statistics including research papers on stochastic algorithms. The content of the book is supported using many exercises and web links. This book will be beneficial for the students who want to research in the field stochastic optimization.


6. “Contributions to a General Asymptotik Statistical Theory” by Pfanzagl Wefelmeyer
“Contributions to a General Asymptotik Statistical Theory” Book Review: The book is a balanced piece of writing presenting both theoretical as well as practical aspects of asymptotik statistical theory. The chapters of this book contain various important topics and also describe tangent cones. The book provides answers to various topics and questions and gives examples of extensive theory on convex tangent cones. Many case studies are featured in this text. The book will be helpful for the students of civil engineering.


7. “Control Theoretic Splines: Optimal Control, Statistics, and Path Planning” by Clyde Martin
“Control Theoretic Splines: Optimal Control, Statistics, and Path Planning” Book Review: The book delicately focuses students, researchers, professionals, and engineers in the development of robotics, computer theory, engineering, econometrics and other areas that require construction of curved sets of raw data. The chapters of this book describe topics like periodic spline, monotone splines, and use of various tools of optimization over vector space in detail. Containing many live study cases this book is seen as a practical approach of computer technology development and solutions of various statistics problems.


8. “Applied Statistics and Probability for Engineers” by Douglas C Montgomery
“Applied Statistics and Probability for Engineers” Book Review: The book gives a clear cut and straight forward idea on statistics. The book is written from both theoretical as well as practical pointofview. It aims at presenting the latest information on practical approaches to problem sets in realistic situations. This book is an excellent resource for students and professionals in statistics, probability, and any area that requires the concepts of physical and chemical sciences. It will be equally important for the students of electrical and mechanical engineering and material sciences.


9. “Probability and Statistical Models: Foundations for Problems in Reliability and Financial Mathematics” by Arjun K Gupta
“Probability and Statistical Models: Foundations for Problems in Reliability and Financial Mathematics” Book Review: The book aims in presenting latest information on fundamental concepts of stochastic modelling. This book also focuses on real time approach of numericals towards solving problems in reliability, insurance, finance and credit risk. The book also offers various concepts in advance learning. The book provides easytograb knowledge to the readers and is written from both theoretical and practical perspectives. And It also includes various projects and their definitions. This book acts as a resource for students and professionals in mathematics, statistics and economics.


10. “Stochastic Differential Games. Theory and Applications” by Chris P Tsokos Kandethody M Ramachandran Tsokos RAMACHANDRAN
“Stochastic Differential Games. Theory and Applications” by Book Review: This book deals with the practical and theoretical knowledge on various theories of finance, economics, and health investments. The chapters broadly cover all the important topics and features mathematical and computational methods. The book presents the latest information on practical approach on problem sets in realistic situations. The book will be an asset for students and professionals of industrial engineering, finance, economics, investment strategies, health sciences, and environment.


11. “The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)” by Trevor Hastie and Robert Tibshirani
“The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)” Book Review: This book describes the important ideas in a variety of fields such as medicine, biology, finance and marketing in a comprehensive manner. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. The many topics include neural networks, support vector machines, classification trees and boosting. It is a valuable learning resource for statisticians and anyone interested in data mining in science or industry.


10. Applied Statistics and Mathematical Statistics
1. “Apllied Statistics and Mathematical Statistics” by S C Gupta
“Applied Statistics and Mathematical Statistics” Book Review: This book is beneficial for degree and postgraduate students. The book contains applications of statistics in industry, economics, agriculture, demography, education and psychology. Mathematical knowledge of calculus is needed to read the book. It has many illustrations and problems. The book covers topics on statistical quality control, time series, index numbers, demand analysis, analysis of variance, design of experiments, design of sample surveys, psychological and educational statistics and vital statistics. Exercises are provided at the end of each chapter for proper reference.


2. “Applied Statistics” by Parimal Mukhopadhyay
“Applied Statistics” Book Review: This book acts as a guide for undergraduate (honours) and postgraduate students of statistics and mathematics. The book is also useful for students of other disciplines like economics, agricultural sciences and engineering.


3. “Methods of Mathematics Applied to Calculus, Probability, and Statistics (Dover Books on Mathematics)” by Richard W Hamming
“Methods of Mathematics Applied to Calculus, Probability, and Statistics (Dover Books on Mathematics)” Book Review: This book covers applications of mathematical methods, topics related to other important fields such as probability and statistics. Knowledge of calculus is needed to understand mathematics in numerous areas. The book contains four part treatment, algebra and analytic geometry, calculus of algebraic functions and transcendental functions and applications. Three helpful appendices and practice answers are mentioned in the book. This book acts as a guide for advanced undergraduates and graduate students and is a practical reference for professionals.


4. “Applied Statistics for Business and Economics” by Robert M Leekley
“Applied Statistics for Business and Economics” Book Review: The book provides students in business and social sciences an effective introduction to some of the most basic techniques available for understanding the world. The calculations can be performed using any standard spreadsheet package present in the book. The book has important examples to reflect reallife situations. The book covers basic probability tools, Bayes’ theorem, sampling, estimation and confidence intervals. The book also describes hypothesis samples, contingency tables, goodnessoffit, analysis of variance and population variances. It covers concepts on the linear relationship between two numeric variables and potentially nonlinear relationships. The book highlights classical timeseries analysis and ways to apply to business and economics. The book provides a practical understanding of statistics. The book will help students in summarizing data using graphs and charts and also make inferences from chapters.


5. “Applied Statistics: A Handbook of Techniques (Springer Series in Statistics)” by Lothar Sachs and Zenon Reynarowych
“Applied Statistics: A Handbook of Techniques (Springer Series in Statistics)” Book Review: This book is useful for research workers and consulting statisticians. The book introduces limited mathematics and important modern statistical methods. Focus is given on the basic principles of statistical formulation and explanation of the conditions under which a certain formula or a certain test is valid. This book is designed for nonmathematicians, technicians, engineers, executives, students, physicians as well as researchers in other disciplines. The book gives preference to the analysis of small sized samples and distributionfree methods. The book contains 440 numerical examples, 57 exercises with solutions, different computational aids, bibliography and a very detailed index. The book gives a mathematician a practical use of statistics. The book also includes 232 mathematical and mathematicalstatistical tables.


6. “Applied Statistics for Business and Management using Microsoft Excel” by Linda Herkenhoff and John Fogli
“Applied Statistics for Business and Management using Microsoft Excel” Book Review: The book highlights capabilities of Microsoft Excel to teach applied statistics. It acts as a guide for students and practitioners who need to master excel to solve practical statistical problems in industry. This book is also useful for students who are mathematically inclined and wary of computers. The book explains students and practitioners to apply excel to statistical techniques in their courses and workplace. The book highlights the powerful computational ability and graphical functions to make learning statistics much easier. Statistical formulas, practice problems with solutions are provided at the end of each chapter to solve business problems.


7. “Computational Electromagnetics (Texts in Applied Mathematics)” by Anders Bondeson and Thomas Rylander
“Computational Electromagnetics (Texts in Applied Mathematics)” Book Review: This book discusses the important computational methods to solve problems in electromagnetics. The book includes “matlab code” throughout. Different techniques and exercises are provided in the book. The book introduces the most popular numerical methods for electromagnetic field, finite difference method, the finite element method and the method of moments. This book is beneficial for undergraduate and beginning graduate students with basic knowledge of electromagnetic field theory, numerical analysis, and MATLABprogramming. Maxwell’s equations, convergence analysis, extrapolation, von Neumann stability analysis and dispersion analysis are highlighted in this book.


8. “Mathematical Foundations of Neuroscience (Interdisciplinary Applied Mathematics)” by G Bard Ermentrout and David H Terman
“Mathematical Foundations of Neuroscience (Interdisciplinary Applied Mathematics)” Book Review: This book highlights methods from nonlinear dynamics to problems in neuroscience. Modern mathematical approaches are used in this book to understand concepts and models of neuronal behaviour. This book is beneficial for the researchers interested in mathematics and neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The book describes numerical, analytical, dynamical systems and perturbation methods. Topics such as noise, multiple time scales and spatial interactions in generating complex activity patterns are mentioned in the book. Basic calculus and differential equations can form the core of a computational neuroscience course. The book contains many illustrations, chapter summaries and exercises in biology, computation and analysis.


9. “Methods of Applied Mathematics (Dover Books on Mathematics)” by Francis Begnaud Hildebrand  
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