Aimed primarily at undergraduate level university students, An Illustrative Introduction to Modern Analysis provides an accessible and lucid contemporary account of the fundamental principles of Mathematical Analysis. The themes treated include Metric Spaces, General Topology, Continuity, Completeness, Compactness, Measure Theory, Integration, Lebesgue Spaces, Hilbert Spaces, Banach Spaces, Linear Operators, Weak and Weak* Topologies. Suitable both for classroom use and independent reading, this book is ideal preparation for further study in research areas where a broad mathematical toolbox is required.

This book is designed as a supplement to an introductory undergraduate or graduate course for mathematics, science and engineering students of all disciplines. the text covers all major aspects of engineering statistics, including descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples and curve fitting, correlation, regression, chi-square tests, and analysis of variance. The book continues to maintain a student-friendly approach and numerical problem solving orientation. Presentations are limited to very basic topics to serve as an introduction to advance topics in those areas of discipline. The purpose of the book is to present the principles and concepts of Probability and Statistics as relevant to student learning.

Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms - When to use them & Why - for Application developers and Researchers Machine Learning from an Application Perspective - General & Machine learning for Healthcare, Education, Business, Engineering Applications Ethics of machine learning including Bias, Fairness, Trust, Responsibility Basics of Deep learning, important deep learning models and applications Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.

A "health disparity" refers to a higher burden of illness, injury, disability, or mortality experienced by one group relative to another. These disparities may be due to many factors including age, income, race, etc. This book will focus on their estimation, ranging from classical approaches including the quantification of a disparity, to more formal modelling, to modern approaches involving more flexible computational approaches. Features: * Presents an overview of methods and applications of health disparity estimation * First book to synthesize research in this field in a unified statistical framework * Covers classical approaches, and builds to more modern computational techniques * Includes many worked examples and case studies using real data * Discusses available software for estimation The book is designed primarily for researchers and graduate students in biostatistics, data science, and computer science. It will also be useful to many quantitative modelers in genetics, biology, sociology, and epidemiology.

- The book discusses the recent techniques in NGS data analysis which is the most needed material by biologists (students and researchers) in the wake of numerous genomic projects and the trend toward genomic research. - The book includes both theory and practice for the NGS data analysis. So, readers will understand the concept and learn how to do the analysis using the most recent programs. - The steps of application workflows are written in a manner that can be followed for related projects. - Each chapter includes worked examples with real data available on the NCBI databases. Programming codes and outputs are accompanied with explanation. - The book content is suitable as teaching material for biology and bioinformatics students. Meets the requirements of a complete semester course on Sequencing Data Analysis Covers the latest applications for Next Generation Sequencing Covers data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics

The number e, the function ex, the logarithmic function in (x) and different hyperbolic functions like cosh (x), sinh (x) make frequent appearances in science and engineering textbooks. Students often fail to appreciate the significance of these mathematical symbols. This book clearly illustrates why such abstract mathematical entities are needed to represent some aspects of physical reality. It provides an overview of different types of numbers and functions along with their historical background and applications. It contains four chapters covering number system, exponential function, logarithmic functions and hyperbolic functions along with the concept of complex angle. Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan or Bhutan)

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences.

How do you divide a line into three? Or five? Or seven? Is there a simple way to marry harmony and geometry? What is the secret diagram alluded to by writers of antiquity? In this groundbreaking book, philosopher Adam Tetlow reveals the long lost Helicon, the master diagram of the ancient arts and crafts.Watch in astonishment as this magical geometric figure produces simple fractions, musical harmonies, Pythagorean triangles, perspective and more. WOODEN BOOKS are small but packed with information. "Fascinating" FINANCIAL TIMES. "Beautiful" LONDON REVIEW OF BOOKS. "Rich and Artful" THE LANCET. "Genuinely mind-expanding" FORTEAN TIMES. "Excellent" NEW SCIENTIST. "Stunning" NEW YORK TIMES. Small books, big ideas.

Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning.

Focusing on the exploration of data with visual methods, this book presents methods and R code for producing high-quality static graphics, interactive visualizations, and animations of time series, spatial, and space-time data. Practical examples using real-world datasets help you understand how to apply the methods and code. Each of the three parts of the book is devoted to different types of data. In each part, the chapters are grouped according to the various visualization methods or data characteristics. Recent developments in the "htmlwidgets" family of packages are covered in this second edition with many new interactive graphics.

Discusses effluent discharges into various ambient waters and predictive tools for design and regulatory purposes. Emphasis placed on numerical modeling and simulations, rather than general examples. Provides real technical solutions and tools for minimizing the impact on coasts and other water bodies. Covers the fundamentals in predicting the mixing of effluents resulting from desalination plants. Includes an introduction to OpenFOAM and its applications.

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Output for each procedure is explained and illustrated, and every output term is defined. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS. This book covers the basics of statistical analysis and addresses more advanced topics such as multidimensional scaling, factor analysis, discriminant analysis, measures of internal consistency, MANOVA (between- and within-subjects), cluster analysis, Log-linear models, logistic regression, and a chapter describing residuals. The end sections include a description of data files used in exercises, an exhaustive glossary, suggestions for further reading, and a comprehensive index. IBM SPSS Statistics 27 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved an invaluable aid to thousands of researchers and students. New to this edition: Screenshots, explanations, and step-by-step boxes have been fully updated to reflect SPSS 27 A new chapter on a priori power analysis helps researchers determine the sample size needed for their research before starting data collection.

Pierri clearly links modern psychoanalytic practice with Freud's interests in the occult using primary sources, some of which have never before been published in English. Assesses the origins of key psychoanalytic ideas.

This study covers comodules, rational modules and bicomodules; cosemisimple, semiperfect and co-Frobenius algebras; bialgebras and Hopf algebras; actions and coactions of Hopf algebras on algebras; finite dimensional Hopf algebras, with the Nicholas-Zoeller and Taft-Wilson theorems and character theory; and more.

Provides a logical framework for considering and evaluating standard setting procedures Covers formal development of a psychometric theory for standard setting Develops logical argument for evaluation procedures for standard setting processes Contains detailed analyses of several standard setting methods Includes problem sets at the ends of chapters that focus on common problems with standard setting methods

CYBERSECURITY LAW Learn to protect your clients with this definitive guide to cybersecurity law in this fully-updated third edition Cybersecurity is an essential facet of modern society, and as a result, the application of security measures that ensure the confidentiality, integrity, and availability of data is crucial. Cybersecurity can be used to protect assets of all kinds, including data, desktops, servers, buildings, and most importantly, humans. Understanding the ins and outs of the legal rules governing this important field is vital for any lawyer or other professionals looking to protect these interests. The thoroughly revised and updated Cybersecurity Law offers an authoritative guide to the key statutes, regulations, and court rulings that pertain to cybersecurity, reflecting the latest legal developments on the subject. This comprehensive text deals with all aspects of cybersecurity law, from data security and enforcement actions to anti-hacking laws, from surveillance and privacy laws to national and international cybersecurity law. New material in this latest edition includes many expanded sections, such as the addition of more recent FTC data security consent decrees, including Zoom, SkyMed, and InfoTrax. Readers of the third edition of Cybersecurity Law will also find: An all-new chapter focused on laws related to ransomware and the latest attacks that compromise the availability of data and systems New and updated sections on new data security laws in New York and Alabama, President Biden's cybersecurity executive order, the Supreme Court's first opinion interpreting the Computer Fraud and Abuse Act, American Bar Association guidance on law firm cybersecurity, Internet of Things cybersecurity laws and guidance, the Cybersecurity Maturity Model Certification, the NIST Privacy Framework, and more New cases that feature the latest findings in the constantly evolving cybersecurity law space An article by the author of this textbook, assessing the major gaps in U.S. cybersecurity law A companion website for instructors that features expanded case studies, discussion questions by chapter, and exam questions by chapter Cybersecurity Law is an ideal textbook for undergraduate and graduate level courses in cybersecurity, cyber operations, management-oriented information technology (IT), and computer science. It is also a useful reference for IT professionals, government personnel, business managers, auditors, cybersecurity insurance agents, and academics in these fields, as well as academic and corporate libraries that support these professions.

Amid recent interest in Clifford algebra for dual quaternions as a more suitable method for Computer Graphics than standard matrix algebra, this book presents dual quaternions and their associated Clifford algebras in a new light, accessible to and geared towards the Computer Graphics community. Collating all the associated formulas and theorems in one place, this book provides an extensive and rigorous treatment of dual quaternions, as well as showing how two models of Clifford algebras emerge naturally from the theory of dual quaternions. Each chapter comes complete with a set of exercises to help readers sharpen and practice their knowledge. This book is accessible to anyone with a basic knowledge of quaternion algebra and is of particular use to forward-thinking members of the Computer Graphics community. .

Revealing the flaws in human decision making, this book explores how AI can be used to optimise decisions for improved business outcomes and efficiency, as well as looking ahead into the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise. Offering an impressive framework of Decision Intelligence (DI), from the theories and concepts used to design autonomous intelligent agents to the technologies that power DI systems and the ways in which companies use decision-making building blocks to build DI solutions that enable businesses to democratise AI, this book provides a systematic approach to AI intelligence and human involvement. Replete with case studies on DI application, as well as wider discussions on the social implications of the technology, this book appeals to both students of AI and data solutions and businesses considering DI adoption.

Geometry of Derivation with Applications is the fifth work in a longstanding series of books on combinatorial geometry (Subplane Covered Nets, Foundations of Translation Planes, Handbook of Finite Translation Planes, and Combinatorics of Spreads and Parallelisms). Like its predecessors, this book will primarily deal with connections to the theory of derivable nets and translation planes in both the finite and infinite cases. Translation planes over non-commutative skewfields have not traditionally had a significant representation in incidence geometry, and derivable nets over skewfields have only been marginally understood. Both are deeply examined in this volume, while ideas of non-commutative algebra are also described in detail, with all the necessary background given a geometric treatment. The book builds upon over twenty years of work concerning combinatorial geometry, charted across four previous books and is suitable as a reference text for graduate students and researchers. It contains a variety of new ideas and generalizations of established work in finite affine geometry and is replete with examples and applications.

This book introduces the fundamentals of the technology satisfaction model (TSM), supporting readers in applying the Rasch model and Structural Equation Modelling (SEM) - a multivariate technique - to higher education (HE) research. User satisfaction is traditionally measured along a single dimension. However, the TSM includes digital technologies for teaching, learning and research across three dimensions: computer efficacy, perceived ease of use and perceived usefulness. Establishing relationships among these factors is a challenge. Although commonly used in psychology to trace relationships, Rasch and SEM approaches are rarely used in educational technology or library and information science. This book, therefore, shows that combining these two analytical tools offers researchers better options for measurement and generalization in HE research. This title presents theoretical and methodological insight of use to researchers in HE.

BIOCALCULUS: CALCULUS, PROBABILITY, AND STATISTICS FOR THE LIFE SCIENCES shows students how calculus relates to biology, with a style that maintains rigor without being overly formal. The text motivates and illustrates the topics of calculus with examples drawn from many areas of biology, including genetics, biomechanics, medicine, pharmacology, physiology, ecology, epidemiology, and evolution, to name a few. Particular attention has been paid to ensuring that all applications of the mathematics are genuine, and references to the primary biological literature for many of these has been provided so that students and instructors can explore the applications in greater depth. Although the focus is on the interface between mathematics and the life sciences, the logical structure of the book is motivated by the mathematical material. Students will come away with a sound knowledge of mathematics, an understanding of the importance of mathematical arguments, and a clear understanding of how these mathematical concepts and techniques are central in the life sciences.

Group sequential methods answer the needs of clinical trial monitoring committees who must assess the data available at an interim analysis. These interim results may provide grounds for terminating the study-effectively reducing costs-or may benefit the general patient population by allowing early dissemination of its findings. Group sequential methods provide a means to balance the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion.
Group Sequential Methods with Applications to Clinical Trials describes group sequential stopping rules designed to reduce average study length and control Type I and II error probabilities. The authors present one-sided and two-sided tests, introduce several families of group sequential tests, and explain how to choose the most appropriate test and interim analysis schedule. Their topics include placebo-controlled randomized trials, bio-equivalence testing, crossover and longitudinal studies, and linear and generalized linear models.
Research in group sequential analysis has progressed rapidly over the past 20 years. Group Sequential Methods with Applications to Clinical Trials surveys and extends current methods for planning and conducting interim analyses. It provides straightforward descriptions of group sequential hypothesis tests in a form suited for direct application to a wide variety of clinical trials. Medical statisticians engaged in any investigations planned with interim analyses will find this book a useful and important tool.

This collection presents the first sustained examination of the nature and status of the idea of principles in early modern thought. Principles are almost ubiquitous in the seventeenth and eighteenth centuries: the term appears in famous book titles, such as Newton's Principia; the notion plays a central role in the thought of many leading philosophers, such as Leibniz's Principle of Sufficient Reason; and many of the great discoveries of the period, such as the Law of Gravitational Attraction, were described as principles. Ranging from mathematics and law to chemistry, from natural and moral philosophy to natural theology, and covering some of the leading thinkers of the period, this volume presents ten compelling new essays that illustrate the centrality and importance of the idea of principles in early modern thought. It contains chapters by leading scholars in the field, including the Leibniz scholar Daniel Garber and the historian of chemistry William R. Newman, as well as exciting, emerging scholars, such as the Newton scholar Kirsten Walsh and a leading expert on experimental philosophy, Alberto Vanzo. The Idea of Principles in Early Modern Thought: Interdisciplinary Perspectives charts the terrain of one of the period's central concepts for the first time, and opens up new lines for further research.

Presents concepts of data for business decision making as well as algorithms and models used to analyze data used to solve business problems. Use data analytics to inform decisions related to product price and possession utilities Market products on the basis of consumer analytics

Features Focus on the foundational theory underpinning Reinforcement Learning Suitable as a primary text for courses in Reinforcement Learning, but also as supplementary reading for applied/financial mathematics, programming, and other related courses Suitable for a professional audience of quantitative analysts or industry specialists Blends theory/mathematics, programming/algorithms and real-world financial nuances while always striving to maintain simplicity and to build intuitive understanding.