Books published by Chapman and Hall/CRC at best prices | Best of Chapman and Hall/CRC (257 books)

Practical Spreadsheet Modeling Using @Risk

Practical Spreadsheet Modeling Using @Risk

Practical Spreadsheet Modeling Using @Risk provides a guide of how to construct applied decision analysis models in spreadsheets. The focus is on the use of Monte Carlo simulation to provide quantitative assessment of uncertainties and key risk drivers. The book presents numerous examples based on real data and relevant practical decisions in a variety of settings, including health care, transportation, finance, natural resources, technology, manufacturing, retail, and Sports and entertainment. All examples involve decision problems where uncertainties make simulation modeling useful to obtain decision insights and explore alternative choices. Good spreadsheet modeling practices are highlighted. The book is suitable for graduate students or advanced undergraduates in business, public policy, health care administration, or any field amenable to simulation modeling of decision problems. The book is also useful for applied practitioners seeking to build or enhance their spreadsheet modeling skills. Features Step-by-step examples of spreadsheet modeling and risk analysis in a variety of fields Description of probabilistic methods, their theoretical foundations, and their practical application in a spreadsheet Environment Extensive example models and exercises based on real data and relevant decision problems Comprehensive use of the @Risk Software for simulation analysis, including a free one-year educational Software license

Rs. 10601.0

The Shape of Space (Textbooks in Mathematics)

The Shape of Space (Textbooks in Mathematics)

The Shape of Space, Third Edition maintains the standard of excellence set by the previous editions. This lighthearted textbook covers the Basic Geometry and topology of two- and three-dimensional spaces―stretching students’ minds as they learn to visualize new possibilities for the shape of our universe. Written by a master expositor, leading researcher in the field, and MacArthur Fellow, its informal exposition and engaging exercises appeal to an exceptionally broad audience, from liberal arts students to math undergraduate and graduate students looking for a clear intuitive understanding to supplement more formal texts, and even to laypeople seeking an entertaining self-study book to expand their understanding of space. Features of the Third Edition: Full-color figures throughout "Picture proofs" have replaced algebraic proofs Simpler handles-and-crosscaps approach to surfaces Updated discussion of cosmological applications Intuitive examples missing from many college and graduate school curricula About the Author: Jeffrey R. Weeks is a freelance geometer living in Canton, New York. With support from the U.S. National Science Foundation, the MacArthur Foundation and several science museums, his work spans pure mathematics, applications in cosmology and―closest to his heart―exposition for the General public.

Rs. 4747.0

Handbook of Homotopy Theory (CRC Press/Chapman and Hall Handbooks in Mathematics Series)

Handbook of Homotopy Theory (CRC Press/Chapman and Hall Handbooks in Mathematics Series)

The Handbook of Homotopy Theory provides a panoramic view of an active area in Mathematics that is currently seeing dramatic solutions to long-standing open problems, and is proving itself of increasing importance across many other mathematical disciplines. The origins of the subject date back to work of Henri Poincaré and Heinz Hopf in the early 20th century, but it has seen enormous progress in the 21st century. A highlight of this volume is an introduction to and diverse applications of the newly established foundational Theory of ¥ -categories. The coverage is vast, ranging from axiomatic to applied, from foundational to computational, and includes surveys of applications both geometric and algebraic. The contributors are among the most active and creative researchers in the field. The 22 chapters by 31 contributors are designed to address novices, as well as established mathematicians, interested in learning the state of the art in this field, whose methods are of increasing importance in many other areas.

Rs. 21428.0

Nonparametric Statistics for Social and Behavioral Sciences

Nonparametric Statistics for Social and Behavioral Sciences

Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM’s SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text:Explains a conceptual framework for each statistical procedurePresents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analysesDiscusses the interpretations of statistical results and conclusions of the researchWith minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.

Rs. 5141.0

Fuzzy Multiple Objective Decision Making

Fuzzy Multiple Objective Decision Making

Multi-objective programming (MOP) can simultaneously optimize multi-objectives in mathematical programming models, but the optimization of multi-objectives triggers the issue of Pareto solutions and complicates the derived answers. To address these problems, researchers often incorporate the concepts of fuzzy sets and evolutionary Algorithms into MOP models.Focusing on the methodologies and applications of this field, Fuzzy Multiple Objective Decision Making presents mathematical tools for complex decision making. The first part of the book introduces the most popular methods used to calculate the solution of MOP in the field of multiple objective decision making (MODM). The authors describe multi-objective evolutionary Algorithms; expand de novo programming to changeable spaces, such as decision and objective spaces; and cover network data envelopment analysis. The second part focuses on various applications, giving readers a practical, in-depth understanding of MODM.A follow-up to the authors’ Multiple Attribute Decision Making: Methods and Applications, this book guides practitioners in using MODM methods to make effective decisions. It also extends students’ knowledge of the methods and provides researchers with the Foundation to publish papers in operations research and Management science journals.

Rs. 5141.0

Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series)

Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series)

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory.  Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful Algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these Algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: ·         Offers a practical and applied introduction to the most popular machine learning methods. ·         Topics covered include feature engineering, resampling, deep learning and more. ·         Uses a hands-on approach and real world data.

Rs. 4923.0

Introduction to Statistical Methods for Clinical Trials (Chapman & Hall/CRC Texts in Statistical Science)

Introduction to Statistical Methods for Clinical Trials (Chapman & Hall/CRC Texts in Statistical Science)

Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.

Rs. 5115.0

Statistical Learning and Data Science (Computer Science and Data Analysis)

Statistical Learning and Data Science (Computer Science and Data Analysis)

Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit.Statistical Learning and Data Science is a work of Reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data.Over the History of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments.

Rs. 5141.0

Principles of Biostatistics

Principles of Biostatistics

This edition is a reprint of the second edition published in 2000 by Brooks/Cole and then Cengage Learning. Principles of Biostatistics is aimed at students in the biological and health sciences who wish to learn modern research methods. It is based on a required course offered at the Harvard School of Public Health. In addition to these graduate students, many health professionals from the Harvard medical area attend as well. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid Foundation has been established makes it easier for the reader to comprehend them. All supplements, including a manual for students with solutions for odd-numbered exercises, a manual for instructors with solutions to all exercises, and selected data sets, are available at http://www.crcpress.com/9781138593145. Marcello Pagano is Professor of Statistical Computing in the Department of Biostatistics at the Harvard School of Public Health. His research in biostatistics is on computer intensive inference and surveillance methods that involve screening methodologies, with their associated laboratory tests, and in obtaining more accurate testing results that use existing technologies. Kimberlee Gauvreau is Associate Professor in the Department of Biostatistics and Associate Professor of Pediatrics at Harvard Medical School. Dr. Gauvreau’s research focuses on biostatistical issues arising in the field of pediatric cardiology. She also works on the development and validation of methods of adjustment for case mix complexity.

Rs. 4854.0

Measuring Society (ASA-CRC Series on Statistical Reasoning in Science and Society)

Measuring Society (ASA-CRC Series on Statistical Reasoning in Science and Society)

Collecting and analyzing data on unemployment, inflation, and inequality help describe the complex world around us. When published by the government, such data are called official Statistics. They are reported by the media, used by politicians to lend weight to their arguments, and by economic commentators to opine about the state of society. Despite such widescale use, explanations about how these measures are constructed are seldom provided for a non-technical reader. This Measuring Society book is a short, accessible guide to six topics: jobs, house prices, inequality, prices for goods and services, poverty, and deprivation. Each relates to concepts we use on a personal level to form an understanding of the society in which we live: We need a job, a place to live, and food to eat. Using data from the United States, we answer three Basic questions: why, how, and for whom these Statistics have been constructed. We add some context and flavor by discussing the historical background. This book provides the reader with a good grasp of these measures. Chaitra H. Nagaraja is an Associate Professor of Statistics at the Gabelli School of Business at Fordham University in New York. Her research interests include house price indices and inequality measurement. Prior to Fordham, Dr. Nagaraja was a researcher at the U.S. Census Bureau. While there, she worked on projects relating to the American Community Survey.

Rs. 2037.0

Bayesian Biostatistics and Diagnostic Medicine

Bayesian Biostatistics and Diagnostic Medicine

There are numerous advantages to using Bayesian methods in diagnostic medicine, which is why they are employed more and more today in clinical studies. Exploring Bayesian Statistics at an introductory level, Bayesian BioStatistics and Diagnostic Medicine illustrates how to apply these methods to solve important problems in medicine and biology. After focusing on the wide range of areas where diagnostic medicine is used, the book introduces Bayesian Statistics and the estimation of accuracy by sensitivity, specificity, and positive and negative predictive values for ordinal and continuous diagnostic measurements. The author then discusses patient covariate information and the statistical methods for estimating the agreement among observers. The book also explains the protocol review process for cancer clinical trials, how tumor responses are categorized, how to use WHO and RECIST criteria, and how Bayesian sequential methods are employed to monitor trials and estimate sample sizes.With many tables and figures, this book enables readers to conduct a Bayesian analysis for a large variety of interesting and practical biomedical problems.

Rs. 8178.0

An Introduction to Systems Biology: Design Principles of Biological Circuits, Second Edition (Chapman & Hall/CRC Mathematical and Computational Biology)

An Introduction to Systems Biology: Design Principles of Biological Circuits, Second Edition (Chapman & Hall/CRC Mathematical and Computational Biology)

Praise for the first edition: … superb, beautifully written and organized work that takes an Engineering approach to Systems biology. Alon provides nicely written appendices to explain the Basic mathematical and biological concepts clearly and succinctly without interfering with the main text. He starts with a mathematical description of transcriptional activation and then describes some Basic transcription-network motifs (patterns) that can be combined to form larger networks. – Nature [This text deserves] serious attention from any quantitative scientist who hopes to learn about modern biology … It assumes no prior knowledge of or even Interest in biology … One final aspect that must be mentioned is the wonderful set of exercises that accompany each chapter. … Alon’s book should become a standard part of the training of graduate students. – Physics Today Written for students and researchers, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological Systems. It highlights simple, recurring circuit elements that make up the regulation of cells and tissues. Rigorously classroom-tested, this edition includes new chapters on exciting advances made in the last decade. Features: Includes seven new chapters The new edition has 189 exercises, the previous edition had 66  Offers new examples relevant to human Physiology and disease

Rs. 4897.0

Multilevel Modeling Using R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Multilevel Modeling Using R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R Software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. New in the Second Edition: Features the use of lmer (instead of lme) and including the most up to date approaches for obtaining confidence intervals for the model parameters. Discusses measures of R2 (the squared multiple correlation coefficient) and overall model fit. Adds a chapter on nonparametric and robust approaches to estimating multilevel models, including rank based, heavy tailed distributions, and the multilevel lasso. Includes a new chapter on multivariate multilevel models. Presents new sections on micro-macro models and multilevel generalized additive models. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research. About the Authors: W. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at Ball State University. Jocelyn E. Bolin is a Professor in the Department of Educational Psychology at Ball State University. Ken Kelley is the Edward F. Sorin Society Professor of IT, Analytics and Operations and the Associate Dean for Faculty and Research for the Mendoza College of Business at the University of Notre Dame.

Rs. 3774.0

Data and Safety Monitoring Committees in Clinical Trials (Chapman & Hall/CRC Biostatistics Series)

Data and Safety Monitoring Committees in Clinical Trials (Chapman & Hall/CRC Biostatistics Series)

Focusing on the practical clinical and statistical issues that arise in pharmaceutical industry trials, this book summarizes the author’s experience in serving on many data monitoring committees (DMCs) and in heading up a contract research organization that provided statistical support to nearly seventy-five DMCs. It explains the difference in DMC operations between the pharmaceutical industry and National Institutes of Health (NIH)-sponsored trials. Leading you through the types of reports for adverse events and lab values, the author presents the statistical requirements of data monitoring committees and gives advice on how statisticians can best interact with physician members of these committees. He also shows how physicians think differently about safety data than statisticians, proving that both views are needed.

Rs. 6700.0

Joint Modeling of Longitudinal and Time-to-Event Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Joint Modeling of Longitudinal and Time-to-Event Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and Software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a Reference book for Scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Rs. 4842.0

Advanced R, Second Edition (Chapman & Hall/CRC The R Series)

Advanced R, Second Edition (Chapman & Hall/CRC The R Series)

Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional, object-oriented, and metaprogramming); and powerful techniques for debugging and optimisingyour code.By reading this book, you will learn: The difference between an object and its name, and why the distinction is important The important vector data structures, how they fit together, and how you can pull them apart using subsetting The fine details of functions and environments The condition system, which powers messages, warnings, and errors The powerful functional programming paradigm, which can replace many for loops The three most important OO systems: S3, S4, and R6 The tidy eval toolkit for metaprogramming, which allows you to manipulate code and control evaluation Effective debugging techniques that you can deploy, regardless of how your code is run How to find and remove performance bottlenecks The second edition is a comprehensive update: New foundational chapters: "Names and values," "Control flow," and "Conditions" comprehensive coverage of object oriented programming with chapters on S3, S4, R6, and how to choose between them Much deeper coverage of metaprogramming, including the new tidy evaluation framework use of new package like rlang (http://rlang.r-lib.org), which provides a clean interface to low-level operations, and purr (http://purrr.tidyverse.org/) for functional programming Use of color in code chunks and figuresHadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages, and ggplot2: Elegant Graphics for Data Analysis.

Rs. 2999.0

Adaptive Design Theory and Implementation Using SAS and R (Chapman & Hall/CRC Biostatistics Series)

Adaptive Design Theory and Implementation Using SAS and R (Chapman & Hall/CRC Biostatistics Series)

Get Up to Speed on Many Types of Adaptive Designs Since the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials. New to the Second Edition Twelve new chapters covering blinded and semi-blinded sample size reestimation design, pick-the-winners design, biomarker-informed adaptive design, Bayesian designs, adaptive multiregional trial design, SAS and R for group sequential design, and much more More analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switching New material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trials Twenty new SAS macros and R functions Enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials Covering even more adaptive designs, this book provides biostatisticians, clinical scientists, and regulatory reviewers with up-to-date details on this innovative area in pharmaceutical research and development. Practitioners will be able to improve the efficiency of their trial design, thereby reducing the time and cost of drug development.

Rs. 7850.79

Geocomputation with R (Chapman & Hall/CRC The R Series)

Geocomputation with R (Chapman & Hall/CRC The R Series)

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will Interest people from many backgrounds, especially Geographic Information Systems (GIS) users Interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users Interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate Reference Systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport Systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport Systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.

Rs. 4643.0

Spatio-Temporal Statistics with R (Chapman & Hall/CRC The R Series)

Spatio-Temporal Statistics with R (Chapman & Hall/CRC The R Series)

The World is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and Time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical Models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal StatisticsProvides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the Literature and available software, providing a bridge for students and researchers alike who wish to learn the Basics of spatio-temporal Statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and Statistics, and who is comfortable with Basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many People as possible the Tools and confidence to analyze spatio-temporal data.

Rs. 4574.0

Introduction to Probability, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Introduction to Probability, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Developed from celebrated Harvard Statistics lectures, Introduction to Probability provides essential language and tools for understanding Statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in Statistics and conditioning to reduce complicated problems to manageable pieces.The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical Software environment. The second edition adds many new examples, exercises, and explanations, to deepen understanding of the ideas, clarify subtle concepts, and respond to feedback from many students and readers. New supplementary Online Resources have been developed, including animations and interactive visualizations, and the book has been updated to dovetail with these resources. Supplementary material is available on Joseph Blitzstein’s website www. stat110.net. The supplements include:Solutions to selected exercisesAdditional practice problemsHandouts including review material and sample exams Animations and interactive visualizations created in connection with the edX Online version of Stat 110.Links to lecture videos available on ITunes U and YouTube There is also a complete instructor's solutions manual available to instructors who require the book for a course.

Rs. 4490.0

Artificial Intelligence for Autonomous Networks (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

Artificial Intelligence for Autonomous Networks (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and Software-defined network/network function virtualization, highlighting the exciting Opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, Software engineers, artificial intelligence, and machine learning researchers.

Rs. 4921.0

The Beauty of Mathematics in Computer Science

The Beauty of Mathematics in Computer Science

The Beauty of Mathematics in Computer Science explains the mathematical fundamentals of Information Technology Products and Services we use every day, from Google Web Search to GPS Navigation, and from Speech recognition to CDMA mobile services. The book was published in Chinese in 2011 and has sold more than 600,000 copies. Readers were surprised to find that many daily-used IT technologies were so tightly tied to mathematical principles. For example, the automatic classification of News articles uses the cosine Law taught in high school. The book Covers many topics related to computer applications and applied Mathematics including: Natural language processing Speech recognition and machine translation Statistical language modeling Quantitive measurement of information Graph Theory and web crawler Pagerank for web search Matrix operation and document classification Mathematical background of big data Neural networks and Google’s deep learning Jun Wu was a staff Research scientist in Google who invented Google’s Chinese, Japanese, and Korean Web Search Algorithms and was responsible for many Google machine learning projects. He wrote official blogs introducing Google technologies behind its Products in very simple Languages for Chinese Internet users from 2006-2010. The blogs had more than 2 million followers. Wu received PhD in computer Science from Johns Hopkins University and has been working on Speech recognition and natural language processing for more than 20 years. He was one of the earliest engineers of Google, managed many Products of the company, and was awarded 19 US patents during his 10-year tenure there. Wu became a full-time VC investor and co-founded Amino Capital in Palo Alto in 2014 and is the author of eight books.

Rs. 3614.0

Artificial Intelligence Safety and Security (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

Artificial Intelligence Safety and Security (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

The History of Robotics and Artificial Intelligence in many ways is also the History of humanity’s attempts to control such technologies. From the Golem of Prague to the Military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent Systems are well publicized but Safety and Security Issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence. The chapters vary in length and technical content from broad Interest opinion Essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.

Rs. 3879.0

Empirical Likelihood Methods in Biomedicine and Health

Empirical Likelihood Methods in Biomedicine and Health

Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of Health Research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the Health sciences, with worked examples using real data. The book material is attractive and easily understandable to scientists who are new to the Research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.

Rs. 7205.0

Books published by Chapman and Hall/CRC at best prices | Best of Chapman and Hall/CRC (257 books)

Books published by Chapman and Hall/CRC at best prices | Best of Chapman and Hall/CRC (257 books) Price
Practical Spreadsheet Modeling Using @Risk Rs. 10601.0
The Shape of Space (Textbooks in Mathematics) Rs. 4747.0
Handbook of Homotopy Theory (CRC Press/Chapman and Hall Handbooks in Mathematics Series) Rs. 21428.0
Nonparametric Statistics for Social and Behavioral Sciences Rs. 5141.0
Fuzzy Multiple Objective Decision Making Rs. 5141.0
Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series) Rs. 4923.0
Introduction to Statistical Methods for Clinical Trials (Chapman & Hall/CRC Texts in Statistical Science) Rs. 5115.0
Statistical Learning and Data Science (Computer Science and Data Analysis) Rs. 5141.0
Principles of Biostatistics Rs. 4854.0
Measuring Society (ASA-CRC Series on Statistical Reasoning in Science and Society) Rs. 2037.0
Bayesian Biostatistics and Diagnostic Medicine Rs. 8178.0
An Introduction to Systems Biology: Design Principles of Biological Circuits, Second Edition (Chapman & Hall/CRC Mathematical and Computational Biology) Rs. 4897.0
Multilevel Modeling Using R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) Rs. 3774.0
Data and Safety Monitoring Committees in Clinical Trials (Chapman & Hall/CRC Biostatistics Series) Rs. 6700.0
Joint Modeling of Longitudinal and Time-to-Event Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) Rs. 4842.0
Advanced R, Second Edition (Chapman & Hall/CRC The R Series) Rs. 2999.0
Adaptive Design Theory and Implementation Using SAS and R (Chapman & Hall/CRC Biostatistics Series) Rs. 7850.79
Geocomputation with R (Chapman & Hall/CRC The R Series) Rs. 4643.0
Spatio-Temporal Statistics with R (Chapman & Hall/CRC The R Series) Rs. 4574.0
Introduction to Probability, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) Rs. 4490.0
Artificial Intelligence for Autonomous Networks (Chapman & Hall/CRC Artificial Intelligence and Robotics Series) Rs. 4921.0
The Beauty of Mathematics in Computer Science Rs. 3614.0
Artificial Intelligence Safety and Security (Chapman & Hall/CRC Artificial Intelligence and Robotics Series) Rs. 3879.0
Empirical Likelihood Methods in Biomedicine and Health Rs. 7205.0