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Doubt over the trustworthiness of published empirical results is not unwarranted and is often a result of statistical mis-specification: invalid probabilistic assumptions imposed on data. Now in its second edition, this bestselling textbook offers a comprehensive course in empirical research methods, teaching the probabilistic and statistical foundations that enable the specification and validation of statistical models, providing the basis for an informed implementation of statistical procedure to secure the trustworthiness of evidence. Each chapter has been thoroughly updated, accounting for developments in the field and the author's own research. The comprehensive scope of the textbook has been expanded by the addition of a new chapter on the Linear Regression and related statistical models. This new edition is now more accessible to students of disciplines beyond economics and includes more pedagogical features, with an increased number of examples as well as review questions and exercises at the end of each chapter.
The essential guide for data scientists and for leaders who must get more from their data science teams The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource." "These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it." --Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy "I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data." --Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University "Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." --A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University
"The worked examples and guided questions are invaluable, and are a particular strength of this text, as they help to prepare the students to tackle the practice questions. Having exam-style questions (at the end) is another very good feature of this book. All of the examples and questions use appropriate and relevant business-related scenarios... I am confident that this book will achieve the aim of helping A/AS Business students develop their maths skills and enhance their understanding of the subject." Michaela Cottee, Principal Lecturer in Statistics, Hertfordshire Business School. If you struggle with calculating profit or working out unit costs, this is the book for you. This textbook companion will help improve your essential maths skills for business, whichever awarding body specification you're following. You can use it throughout your course, whenever you feel you need some extra help. - Develop your understanding of both maths and business with all worked examples and questions within a business context - Improve your confidence with a step-by-step approach to every maths skill - Measure your progress with guided and non-guided questions to see how you're improving - Understand where you're going wrong with full worked solutions to every question - Feel confident in expert guidance from experienced teacher Charlotte Wright and Principal Examiner Mike Pickerden; reviewed by Dr Michaela Cottee, Principal Lecturer in Statistics at Hertfordshire Business School
The last fifteen years have seen a flurry of exciting developments in Fourier restriction theory, leading to significant new applications in diverse fields. This timely text brings the reader from the classical results to state-of-the-art advances in multilinear restriction theory, the Bourgain-Guth induction on scales and the polynomial method. Also discussed in the second part are decoupling for curved manifolds and a wide variety of applications in geometric analysis, PDEs (Strichartz estimates on tori, local smoothing for the wave equation) and number theory (exponential sum estimates and the proof of the Main Conjecture for Vinogradov's Mean Value Theorem). More than 100 exercises in the text help reinforce these important but often difficult ideas, making it suitable for graduate students as well as specialists. Written by an author at the forefront of the modern theory, this book will be of interest to everybody working in harmonic analysis.
Exam Board: OCR Level: A-level Subject: Mathematics First Teaching: September 2017 First Exam: June 2018 An OCR endorsed textbook Boost your students' knowledge, skills and understanding so that they can reason and apply mathematical techniques in solving problems; with resources developed specifically for the OCR specification by subject experts and in conjunction with MEI (Mathematics in Education and Industry). - Boosts students' confidence approaching assessment with plenty of practice questions and skill-focused exercises. - Build connections between topics with points of interest and things to notice such as links to real world examples and noticing patterns in the mathematics. - Ensure targeted development of problem-solving, proof and modelling with dedicated sections on these key areas. - Help students to overcome misconceptions and develop insight into problem-solving with annotated worked examples. - Enhance individual understanding with discussion points designed for the classroom and end of chapter summaries of the key points. - Tackle the new statistics requirements with five dedicated statistics chapters and questions around the use of large data sets. - Address the use of technology in Mathematics with a variety of questions based around the use of spreadsheets, graphing software and graphing calculators. - Provide clear paths of progression that combine pure and applied maths into a coherent whole.
Contests are prevalent in many areas, including sports, rent seeking, patent races, innovation inducement, labor markets, scientific projects, crowdsourcing and other online services, and allocation of computer system resources. This book provides unified, comprehensive coverage of contest theory as developed in economics, computer science, and statistics, with a focus on online services applications, allowing professionals, researchers and students to learn about the underlying theoretical principles and to test them in practice. The book sets contest design in a game-theoretic framework that can be used to model a wide-range of problems and efficiency measures such as total and individual output and social welfare, and offers insight into how the structure of prizes relates to desired contest design objectives. Methods for rating the skills and ranking of players are presented, as are proportional allocation and similar allocation mechanisms, simultaneous contests, sharing utility of productive activities, sequential contests, and tournaments.
Undergraduate students with no prior classroom instruction in mathematical logic will benefit from this evenhanded multipart text by one of the centuries greatest authorities on the subject. Part I offers an elementary but thorough overview of mathematical logic of first order. The treatment does not stop with a single method of formulating logic; students receive instruction in a variety of techniques, first learning model theory (truth tables), then Hilbert-type proof theory, and proof theory handled through derived rules. Part II supplements the material covered in Part I and introduces some of the newer ideas and the more profound results of logical research in the twentieth century. Subsequent chapters introduce the study of formal number theory, with surveys of the famous incompleteness and undecidability results of Gödel, Church, Turing, and others. The emphasis in the final chapter reverts to logic, with examinations of Gödel's completeness theorem, Gentzen's theorem, Skolem's paradox and nonstandard models of arithmetic, and other theorems. Unabridged republication of the edition published by John Wiley & Sons, Inc. New York, 1967. Preface. Bibliography. Theorem and Lemma Numbers: Pages. List of Postulates. Symbols and Notations. Index.
A formal model in the social sciences builds explanations when it structures the reasoning underlying a theoretical argument, opens venues for controlled experimentation, and leads to hypotheses. Yet more importantly, models evaluate theory, build theory, and enhance conjectures. Formal Modeling in Social Science addresses the varied helpful roles of formal models and goes further to take up more fundamental considerations of epistemology and methodology.The authors integrate the exposition of the epistemology and the methodology of modeling and argue that these two reinforce each other. They illustrate the process of designing an original model suited to the puzzle at hand, using multiple methods in diverse substantive areas of inquiry. The authors also emphasize the crucial, though underappreciated, role of a narrative in the progression from theory to model. Transparency of assumptions and steps in a model means that any analyst will reach equivalent predictions whenever she replicates the argument. Hence, models enable theoretical replication, essential in the accumulation of knowledge. Formal Modeling in Social Science speaks to scholars in different career stages and disciplines and with varying expertise in modeling.
An authoritative textbook based on the legendary economics course taught at the University of Chicago Price theory is a powerful analytical toolkit for measuring, explaining, and predicting human behavior in the marketplace. This incisive textbook provides an essential introduction to the subject, offering a diverse array of practical methods that empower students to learn by doing. Based on Economics 301, the legendary PhD course taught at the University of Chicago, the book emphasizes the importance of applying price theory in order to master its concepts. Chicago Price Theory features immersive chapter-length examples such as addictive goods, urban-property pricing, the consequences of prohibition, the value of a statistical life, and occupational choice. It looks at human behavior in the aggregate of an industry, region, or demographic group, but also provides models of individuals when they offer insights about the aggregate. The book explains the surprising answers that price theory can provide to practical questions about taxation, education, the housing market, government subsidies, and much more. Emphasizes the application of price theory, enabling students to learn by doing Features chapter-length examples such as addictive goods, urban-property pricing, the consequences of prohibition, and the value of a statistical life Supported by video lectures taught by Kevin M. Murphy and Gary Becker The video course enables students to learn the theory at home and practice the applications in the classroom
Statistical designs, sample surveys and evaluation designs are fundamental tools for solving queries related to population parameters and the effects of public programs and policies. This book explores the concepts of effective sampling and evaluation techniques in a cohesive and concise manner. Sampling design techniques, including simple random sampling, stratified sampling, systematic sampling and cluster sampling, are presented in detail. These techniques play a vital role when choosing an appropriate sample survey design. The concepts of multistage design, non-sampling errors and evaluation techniques including before-after design, one-time treatment and control design are discussed extensively. The book focuses on different methods of estimation, including multiple regression analysis and logistic regression. It covers the issue of bias in a design, the source of such bias and ways to overcome it. Clear guidelines with remedial measures are outlined to facilitate choosing a suitable sampling design.
Written in easy to understand language, this self-explanatory guide introduces the fundamentals of finite element methods and its application to differential equations. Beginning with a brief introduction to Sobolev spaces and elliptic scalar problems, the text progresses through an explanation of finite element spaces and estimates for the interpolation error. The concepts of finite element methods for parabolic scalar parabolic problems, object-oriented finite element algorithms, efficient implementation techniques, and high dimensional parabolic problems are presented in different chapters. Recent advances in finite element methods, including non-conforming finite elements for boundary value problems of higher order and approaches for solving differential equations in high dimensional domains are explained for the benefit of the reader. Numerous solved examples and mathematical theorems are interspersed throughout the text for enhanced learning.
Exam Board: SQA Level: Higher Subject: Maths First Teaching: 2014, First Exam: 2015 This CfE Higher Maths Grade Booster is the essential guide to exam skills. It includes detailed advice on how to approach and answer the different types of question you will find in the exam and has been written by an experienced teacher and exam expert. * Detailed advice on how to approach all the different types of question you will find in the exam will develop your skills and help you to avoid common pitfalls * Essential guide to structuring your responses shows you how to formulate and improve your answers * Worked examples of weak and strong answers let you see exactly where and how marks are gained and how to get the best result * A dedicated chapter on the Assignment ensures that you have a great foundation for your grade before you even enter the exam room
This first introductory text to discrete integrable systems introduces key notions of integrability from the vantage point of discrete systems, also making connections with the continuous theory where relevant. While treating the material at an elementary level, the book also highlights many recent developments. Topics include: Darboux and Backlund transformations; difference equations and special functions; multidimensional consistency of integrable lattice equations; associated linear problems (Lax pairs); connections with Pade approximants and convergence algorithms; singularities and geometry; Hirota's bilinear formalism for lattices; intriguing properties of discrete Painleve equations; and the novel theory of Lagrangian multiforms. The book builds the material in an organic way, emphasizing interconnections between the various approaches, while the exposition is mostly done through explicit computations on key examples. Written by respected experts in the field, the numerous exercises and the thorough list of references will benefit upper-level undergraduate, and beginning graduate students as well as researchers from other disciplines.
This book can form the basis of a second course in algebraic geometry. As motivation, it takes concrete questions from enumerative geometry and intersection theory, and provides intuition and technique, so that the student develops the ability to solve geometric problems. The authors explain key ideas, including rational equivalence, Chow rings, Schubert calculus and Chern classes, and readers will appreciate the abundant examples, many provided as exercises with solutions available online. Intersection is concerned with the enumeration of solutions of systems of polynomial equations in several variables. It has been an active area of mathematics since the work of Leibniz. Chasles' nineteenth-century calculation that there are 3264 smooth conic plane curves tangent to five given general conics was an important landmark, and was the inspiration behind the title of this book. Such computations were motivation for Poincare's development of topology, and for many subsequent theories, so that intersection theory is now a central topic of modern mathematics.
Written for the Math for Liberal Arts course, TOPICS IN CONTEMPORARY MATHEMATICS, 10e, International Edition helps students see math at work in the world by presenting problem solving in purposeful and meaningful contexts. Many of the problems in the text demonstrate how math relates to subjects-such as sociology, psychology, business, and technology-that generally interest students.
The self-taught mathematician Hua Loo-Keng (1910 1985) has been credited with inspiring generations of mathematicians, while his papers on number theory are regarded as some of the most significant contributions made to the subject during the first half of the twentieth century. An Introduction to Higher Mathematics is based on the lectures given by Hua at the University of Science and Technology of China from 1958. The course reflects Hua's instinctive technique, using the simplest tools to tackle even the most difficult problems, and contains both pure and applied mathematics, emphasising the interdependent relationships between different branches of the discipline. With hundreds of diagrams, examples and exercises, this is a wide-ranging reference text for university mathematics and a testament to the teaching of one of the most eminent mathematicians of his generation.
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an "Introduction to Data Science" course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains "War Stories," offering perspectives on how data science applies in the real world Includes "Homework Problems," providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides "Take-Home Lessons," emphasizing the big-picture concepts to learn from each chapter Recommends exciting "Kaggle Challenges" from the online platform Kaggle Highlights "False Starts," revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show "The Quant Shop" (www.quant-shop.com)
This text offers an excellent introduction to the mathematical theory of wavelets for senior undergraduate students. Despite the fact that this theory is intrinsically advanced, the author's elementary approach makes it accessible at the undergraduate level. Beginning with thorough accounts of inner product spaces and Hilbert spaces, the book then shifts its focus to wavelets specifically, starting with the Haar wavelet, broadening to wavelets in general, and culminating in the construction of the Daubechies wavelets. All of this is done using only elementary methods, bypassing the use of the Fourier integral transform. Arguments using the Fourier transform are introduced in the final chapter, and this less elementary approach is used to outline a second and quite different construction of the Daubechies wavelets. The main text of the book is supplemented by more than 200 exercises ranging in difficulty and complexity.
Rich selection of 100 practice problems-with hints and solutions-for students preparing for the William Lowell Putnam and other undergraduate-level mathematical competitions. Real numbers, differential equations, integrals, polynomials, sets, other topics. Hours of stimulating challenge for math buffs at varying degrees of proficiency. References.
Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing results using various modeling options. Common pitfalls, data issues, and interpretation of model results are also addressed. Programs in both R and SAS are made available for all results presented in the text so that readers can emulate and adapt analyses for their own data analysis needs. Data, R, and SAS scripts can be found online at http://www.spesi.org.
Developed specifically for students in the behavioral and brain sciences, this is the only textbook that provides an accessible and practical overview of the range of human neuroimaging techniques. Methods covered include functional and structural magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, multimodal imaging, and various brain stimulation methods. Experimental design, image processing, and statistical inference are also addressed, with chapters for both basic and more advanced data analyses. Key concepts are illustrated through research studies on the relationship between brain and behavior, and practice questions are included throughout to test knowledge and aid self-study. Offering just the right amount of detail for understanding how major imaging techniques can be applied to answer neuroscientific questions, and the practical skills needed for future research, this is an essential text for advanced undergraduate and graduate students in psychology, neuroscience, and cognitive science programs taking introductory courses on human neuroimaging.
The formula that transforms the probability of success when growing your business with M&A The M&A Formula brings together decades of research and case studies from recognised leaders into a model that anybody can use to grow their business using M&A, no matter large or small. Whether you see it as avoiding the painful failure that currently runs at a Global average of over 50%, or stacking the cards in your favour, business model-driven M&A will definitely help you win by either seizing opportunities from your competition, or failing fast - before it really hurts you. M&As fail because the thinking surrounding them fails the rigour of scientific examination; by observing the results of conventional processes and positions, the need for new direction becomes apparent. This book presents a new set of tactics based on data from high-profile M&As, constructing a modern map of practical and business model-driven tactics that succeed in the real world. Case studies of successful deals illustrate on-the-ground implementation of a new M&A model, and tactics formulated by M&A specialists equip you with the wisdom to avoid common pitfalls and costly errors. The M&A sector is continuing to grow, and the trend shows no sign of slowing. Business leaders need a robust, business model-driven M&A strategy for handling these high-stakes transactions, but the usual methods are no longer cutting it. This book provides a new way forward for businesses seeking smart M&A tactics, helping them to: Rethink conventional M&A wisdom in light of recent failures. Adopt new data-backed tactics that help ensure success. Avoid litigation risk and the high cost of failures. Examine practical models and illustrative high-profile case studies. M&A failures have reached global epidemic proportions, with economic impacts to scale. Businesses around the world are in dire need of direction, and as the stakes grow, so do the potential costs of mistakes. The M&A Formula provides sound guidance and a practical new model for successful M&As in the new economy.
Intended for precalculus courses requiring a graphing calculator, Functions and Change emphasizes the application of mathematics to real problems students encounter each day. Applications from a variety of disciplines, including Astronomy, Biology, and the Social Sciences, make concepts interesting for students who have difficulty with more theoretical coverage of mathematics. In addition to these meaningful applications, the authors' easy-to-read writing style allows students to see mathematics as a descriptive problem-solving tool. An extended version of the successful Functions and Change: A Modeling Approach to College Algebra, this text includes three chapters of trigonometry.
Unique in its clarity, examples, and range, Physical Mathematics explains simply and succinctly the mathematics that graduate students and professional physicists need to succeed in their courses and research. The book illustrates the mathematics with numerous physical examples drawn from contemporary research. This second edition has new chapters on vector calculus, special relativity and artificial intelligence and many new sections and examples. In addition to basic subjects such as linear algebra, Fourier analysis, complex variables, differential equations, Bessel functions, and spherical harmonics, the book explains topics such as the singular value decomposition, Lie algebras and group theory, tensors and general relativity, the central limit theorem and Kolmogorov's theorems, Monte Carlo methods of experimental and theoretical physics, Feynman's path integrals, and the standard model of cosmology.
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.
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