What's new in the Second Edition? 1. Fully compliant with the latest version of SPSS version 12 2. More coverage of advanced statistics including completely new coverage of non-parametric statistics. The book is 50 per cent longer than the First Edition. 3. Each section of each chapter now has a notation - 1,2 or 3 - referring to the intended level of study. This helps students navigate their way through the book and makes it user-friendly for students of ALL levels. 4. Has a 'how to use this book' section at the start of the text. 5. Characters in each chapter have defined roles - summarizing key points, to pose questions etc 6. Each chapter now has several examples for students to work through. Answers provided on the enclosed CD-ROM

    Clear, comprehensive coverage of utility theory, 2-person zero-sum games, 2-person non-zero-sum games, n-person games, individual and group decision-making, more. Bibliography.

    No one can stop him--but he walks away. A miracle? No...dysentery. Microbes saved the Roman Empire. Nearly a millennium later, the microbes of the Black Death ended the Middle Ages, making possible the Renaissance, western democracy, and the scientific revolution. Soon after, microbes ravaged the Americas, paving the way for their European conquest. Again and again, microbes have shaped our health, our genetics, our history, our culture, our politics, even our religion and ethics. This book reveals much that scientists and cultural historians have learned about the pervasive interconnections between infectious microbes and humans. It also considers what our ongoing fundamental relationship with infectious microbes might mean for the future of the human species. The "good side" of history's worst epidemics The surprising debt we owe to killer diseases Where diseases came from... ...and where they may be going Children of pestilence: disease and civilization From Egypt to Mexico, the Romans to Attila the Hun STDs, sexual behavior, and culture How microbes may shape cultural cycles of puritanism and promiscuity

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

    

    The universe is all about extremes, and in this engaging and thought-provoking book, astronomer Bryan Gaensler gives a whirlwind tour of the galaxies, with an emphasis on its fastest, hottest, heaviest, brightest, oldest, densest, and even loudest elements. From supernova explosions a billion times brighter than the sun to an asteroid the size of a beach ball, Extreme Cosmos offers a fascinating, fresh, and informed perspective of the remarkable richness of the universe, and the incredible physics that modern astronomy has revealed.

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    If it takes a book to get it across, I hope this book will do it. It ought to.”—Thomas Schelling, Distinguished University Professor, School of Public Policy, University of Maryland, and 2005 Nobel Prize Laureate in Economics “With humor, insight, piercing logic and a nod to history, Ziliak and McCloskey show how economists—and other scientists—suffer from a mass delusion about statistical analysis. The quest for statistical significance that pervades science today is a deeply flawed substitute for thoughtful analysis. . . . Yet few participants in the scientific bureaucracy have been willing to admit what Ziliak and McCloskey make clear: the emperor has no clothes.”—Kenneth Rothman, Professor of Epidemiology, Boston University School of Health The Cult of Statistical Significance shows, field by field, how “statistical significance,” a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ “testing” that doesn’t test and “estimating” that doesn’t estimate. The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots. Stephen T. Ziliak is the author or editor of many articles and two books. He currently lives in Chicago, where he is Professor of Economics at Roosevelt University. Deirdre N. McCloskey, Distinguished Professor of Economics, History, English, and Communication at the University of Illinois at Chicago, is the author of twenty books and three hundred scholarly articles. She has held Guggenheim and National Humanities Fellowships. She is best known for How to Be Human* Though an Economist (University of Michigan Press, 2000) and her most recent book, The Bourgeois Virtues: Ethics for an Age of Commerce (2006).

    The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your dataWonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language--one practical example at a time.--Jeffrey Ryan, software consultant and R package author

    But for those of us who left math behind in high school, the numbers and figures hurled at us as we go about our days can sometimes leave us scratching our heads and feeling as if we’re fumbling through a mathematical minefield. In this eye-opening and extraordinarily accessible book, mathemati­cian Kit Yates illuminates hidden principles that can help us understand and navigate the chaotic and often opaque surfaces of our world. In The Math of Life and Death, Yates takes us on a fascinating tour of everyday situations and grand-scale applications of mathematical concepts, including exponential growth and decay, optimization, statistics and probability, and number systems. Along the way he reveals the mathematical undersides of controversies over DNA testing, medical screening results, and historical events such as the Chernobyl disaster and the Amanda Knox trial. Readers will finish this book with an enlightened perspective on the news, the law, medicine, and history, and will be better equipped to make personal decisions and solve problems with math in mind, whether it’s choosing the shortest checkout line at the grocery store or halting the spread of a deadly disease.

    gross domestic product by 2020. In Drugs for Life, Joseph Dumit considers how our burgeoning consumption of medicine and cost of healthcare not only came to be, but also came to be taken for granted. For several years, Dumit attended pharmaceutical industry conferences; spoke with marketers, researchers, doctors, and patients; and surveyed the industry's literature regarding strategies to expand markets for prescription drugs. He concluded that underlying the continual growth in medications, disease categories, costs, and insecurity is a relatively new perception of ourselves as inherently ill and in need of chronic treatment. This perception is based on clinical trials that we have largely outsourced to pharmaceutical companies. Those companies in turn see clinical trials as investments and measure the value of those investments by the size of the market and profits that they will create. They only ask questions for which the answer is more medicine. Drugs for Life challenges our understanding of health, risks, facts, and clinical trials, the very concepts used by pharmaceutical companies to grow markets to the point where almost no one can imagine a life without prescription drugs.

    The presentation stresses analytical methods, concrete examples, and geometric intuition. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory.About the Author:Steven Strogatz is in the Center for Applied Mathematics and the Department of Theoretical and Applied Mathematics at Cornell University. Since receiving his Ph.D. from Harvard university in 1986, Professor Strogatz has been honored with several awards, including the E.M. Baker Award for Excellence, the highest teaching award given by MIT.

    In college, I ran against Kenyans, and wondered whether endurance genes might have traveled with them from East Africa. At the same time, I began to notice that a training group on my team could consist of five men who run next to one another, stride for stride, day after day, and nonetheless turn out five entirely different runners. How could this be?We all knew a star athlete in high school. The one who made it look so easy. He was the starting quarterback and shortstop; she was the all-state point guard and high-jumper. Naturals. Or were they?The debate is as old as physical competition. Are stars like Usain Bolt, Michael Phelps, and Serena Williams genetic freaks put on Earth to dominate their respective sports? Or are they simply normal people who overcame their biological limits through sheer force of will and obsessive training?The truth is far messier than a simple dichotomy between nature and nurture. In the decade since the sequencing of the human genome, researchers have slowly begun to uncover how the relationship between biological endowments and a competitor’s training environment affects athleticism. Sports scientists have gradually entered the era of modern genetic research.In this controversial and engaging exploration of athletic success, Sports Illustrated senior writer David Epstein tackles the great nature vs. nurture debate and traces how far science has come in solving this great riddle. He investigates the so-called 10,000-hour rule to uncover whether rigorous and consistent practice from a young age is the only route to athletic excellence.Along the way, Epstein dispels many of our perceptions about why top athletes excel. He shows why some skills that we assume are innate, like the bullet-fast reactions of a baseball or cricket batter, are not, and why other characteristics that we assume are entirely voluntary, like an athlete’s will to train, might in fact have important genetic components.This subject necessarily involves digging deep into sensitive topics like race and gender. Epstein explores controversial questions such as:Are black athletes genetically predetermined to dominate both sprinting and distance running, and are their abilities influenced by Africa’s geography?Are there genetic reasons to separate male and female athletes in competition?Should we test the genes of young children to determine if they are destined for stardom?Can genetic testing determine who is at risk of injury, brain damage, or even death on the field?Through on-the-ground reporting from below the equator and above the Arctic Circle, revealing conversations with leading scientists and Olympic champions, and interviews with athletes who have rare genetic mutations or physical traits, Epstein forces us to rethink the very nature of athleticism.

    Imagine that you face three doors, behind one of which is a prize. You choose one but do not open it. The host--call him Monty Hall--opens a different door, alwayschoosing one he knows to be empty. Left with two doors, will you do better by sticking with your first choice, or by switching to the other remaining door? In this light-hearted yet ultimately serious book, Jason Rosenhouse explores the history of this fascinating puzzle. Using a minimum ofmathematics (and none at all for much of the book), he shows how the problem has fascinated philosophers, psychologists, and many others, and examines the many variations that have appeared over the years. As Rosenhouse demonstrates, the Monty Hall Problem illuminates fundamental mathematical issuesand has abiding philosophical implications. Perhaps most important, he writes, the problem opens a window on our cognitive difficulties in reasoning about uncertainty.

    The invaluable companion to the new edition of the bestselling How to Measure Anything This companion workbook to the new edition of the insightful and eloquent How to Measure Anything walks readers through sample problems and exercises in which they can master and apply the methods discussed in the book.The book explains practical methods for measuring a variety of intangibles, including approaches to measuring customer satisfaction, organizational flexibility, technology risk, technology ROI, and other problems in business, government, and not-for-profits.Companion to the revision of the bestselling How to Measure AnythingProvides chapter-by-chapter exercises Written by industry leader Douglas Hubbard Written by recognized expert Douglas Hubbard--creator of Applied Information Economics--How to Measure Anything Workbook illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.