With help from Dr. Seuss and Cookie Monster, she explains why numbers can’t be objective: in order to count, one must first decide what counts. Every number is the ending to a story built on cultural assumptions, social conventions, and personal judgments.And yet, in this age of big data and metric mania, numbers shape almost every facet of our lives: whether we get hired, fired, or promoted; whether we get into college or out of prison; how our opinions are gathered and portrayed to politicians; or how government designs health and safety regulations. In warm and playful prose, Counting explores what happens when we measure nebulous notions like merit, race, poverty, pain, or productivity.When so much rides on numbers, they can become instruments of social welfare, justice, and democracy—or not. The citizens of Flint, Michigan, for instance, used numbers to prove how their household water got contaminated and to force their government to take remedial action. In stark contrast, the Founding Fathers finessed an intractable conflict by counting each slave as three-fifths of a person in the national census. They set a terrible precedent for today’s politicians who claim to solve moral and political dilemmas with arithmetic.Suffused with moral reflection and ending with a powerful epilogue on COVID-19’s dizzying statistics, Counting will forever change our relationship with numbers.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    For almost 500 years, the masses have been thoroughly deceived by a cosmic fairy-tale of astronomical proportions. We have been taught a falsehood so gigantic and diabolical that it has blinded us from our own experience and common sense, from seeing the world and the universe as they truly are. Through pseudo-science books and programs, mass media and public education, universities and government propaganda, the world has been systematically brain-washed, slowly indoctrinated over centuries into the unquestioning belief of the greatest lie of all time. A multi-generational conspiracy has succeeded, in the minds of the masses, to pick up the fixed Earth, shape it into a ball, spin it in circles, and throw it around the Sun! The greatest cover-up of all time, NASA and Freemasonry's biggest secret, is that we are living on a plane, not a planet, that Earth is the flat, stationary center of the universe.

    Readers profit from its verbal-conceptual exposition and frequent use of examples.The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 .Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

    From the movement of flocks of birds to the Internet, environmental sustainability, and market regulation, the study and understanding of complex non-linear systems has become highly influential over the last 30 years.In this Very Short Introduction, one of the leading figures in the field, John Holland, introduces the key elements and conceptual framework of complexity. From complex physical systems such as fluid flow and the difficulties of predicting weather, to complex adaptive systems such as the highly diverse and interdependent ecosystems of rainforests, he combines simple, well-known examples -- Adam Smith's pin factory, Darwin's comet orchid, and Simon's 'watchmaker' -- with an account of the approaches, involving agents and urn models, taken by complexity theory.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

    Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.

    Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, multistage inference, social perception, medical diagnosis, risk perception, and methods for correcting and improving judgments under uncertainty. About half of the chapters are edited versions of classic articles; the remaining chapters are newly written for this book. Most review multiple studies or entire subareas of research and application rather than describing single experimental studies. This book will be useful to a wide range of students and researchers, as well as to decision makers seeking to gain insight into their judgments and to improve them.

    Including a selection of exercises, adjusted for this edition, at the end of each chapter, it offers a new and simpler treatment of the representability of recursive functions, a traditional stumbling block for students on the way to the Godel incompleteness theorems.

    Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

    Called by some, "the theory of everything," superstrings may solve a problem that has eluded physicists for the past 50 years, the final unification of the two great theories of the twentieth century, general relativity and quantum field theory. Now, here is a thoroughly revised, second edition of a course-tested comprehensive introductory graduate text on superstrings which stresses the most current areas of interest, not covered in other presentations, including: - Four-dimensional superstrings - Kac-Moody algebras - Teichm�ller spaces and Calabi-Yau manifolds - M-theory Membranes and D-branes - Duality and BPS relations - Matrix models The book begins with a simple discussion of point particle theory, and uses Feynman path integrals to unify the presentation of superstrings. It has been updated throughout, and three new chapters on M-theory have been added. Prerequisites are an acquaintance with quantum mechanics and relativity.

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    It focuses squarely on the inherent irrationality of religion, and reveals its utter irreconcilability with science. Offering several "reconciliation theories" to people of faith, it forces every reader to make a choice.Contents The Reason Revolution in historical context Questioning belief Reasons for skepticism Secular humanism as an alternative worldview Political implications of atheism The collapse of religion Hopeful predictions Reconciliation theories Comments by clergyCall to action

    It is intended to provide the essential primary texts for students of logic, metaphysics and philosophy of language.It contains, in particular, Frege's four essays 'Function and Concept', 'On Sinn and Bedeutung', 'On Concept and Object' and 'Thought', and new translations of key parts of the Begriffschrift, Grundlagen and Grundgesetze. Additional selections have also been made from his Collected Papers, Posthumous Writings and Correspondence. The editor's introduction provides an overview of the development and significance of Frege's philosophy, highlighting some of the main issues of interpretation. Footnotes, appendices and other editorial material have been supplied to facilitate understanding of the works of one of the central figures in modern philosophy.

    His conception of the universe pervades Christian theology. Knowledge of his thought is necessary to understand Bacon, Galileo, and the modern scientific view of nature, as well as Dante and many passages from Chaucer, Shakespeare, and Milton. Many phrases such as liberal education and theory contrasted with practice originated with this student of Plato and tutor of Alexander the Great.Writing to inform the beginner and stimulate the expert, eminent scholar A. E. Taylor presents a searching analysis of Aristotle's thought, including classification of the sciences; formal logic; theory of knowledge; matter and form; the four causes; God; physics; biology; sensation; ethics; theory of the state; and the fine arts. He also considers Aristotle's provincialism, errors regarding the nervous system and astronomy, and defense of slavery.The Giants of Philosophy is a series of dramatic presentations, in understandable language, of the concerns, questions, interests, and overall world view of history's greatest philosophers. Special emphasis on clear and relevant explanations gives you a new arsenal of insights toward living a better life.