Along the way we’ll learn how selection bias can explain why your boss doesn’t know he sucks (even when everyone else does); how to use Bayes’ Theorem to decide if your partner is cheating on you; and why Mark Zuckerberg should never be used as an example for anything. See the world in a whole new light, and make better decisions and judgements without ever going near a t-test. Think. Think Statistically.

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    Donations cover the cost of registration and a uniform for a child in need. AYSO Soccer is a family experience and an opportunity to create memories for a lifetime. The positive environment of AYSO is the right place for kids to learn soccer, but it’s also where they learn important life lessons, social skills and get active.

    With its unique combination of Japanese-style comics called manga and serious educational content, the EduManga format is already a hit in Japan.In The Manga Guide to Statistics, our heroine Rui is determined to learn about statistics to impress the dreamy Mr. Igarashi and begs her father for a tutor. Soon she's spending her Saturdays with geeky, bespectacled Mr. Yamamoto, who patiently teaches her all about the fundamentals of statistics: topics like data categorization, averages, graphing, and standard deviation.After all her studying, Rui is confident in her knowledge of statistics, including complex concepts like probability, coefficients of correlation, hypothesis tests, and tests of independence. But is it enough to impress her dream guy? Or maybe there's someone better, right in front of her?Reluctant statistics students of all ages will enjoy learning along with Rui in this charming, easy-to-read guide, which uses real-world examples like teen magazine quizzes, bowling games, test scores, and ramen noodle prices. Examples, exercises, and answer keys help you follow along and check your work. An appendix showing how to perform statistics calculations in Microsoft Excel makes it easy to put Rui's lessons into practice.This EduManga book is a translation from a bestselling series in Japan, co-published with Ohmsha, Ltd. of Tokyo, Japan.

    Although deeply influenced by Einstein, he was also, more unusually for a scientist, inspired by mysticism. Indeed, in the 1970s and 1980s he made contact with both J. Krishnamurti and the Dalai Lama whose teachings helped shape his work. In both science and philosophy, Bohm's main concern was with understanding the nature of reality in general and of consciousness in particular. In this classic work he develops a theory of quantum physics which treats the totality of existence as an unbroken whole. Writing clearly and without technical jargon, he makes complex ideas accessible to anyone interested in the nature of reality.

    Recently he set out to travel through Pakistan, revisiting those places that meant most to him along the great Indus river, from its delta on the Arabian Sea to its headwaters in the Himalayas, by way of the mysterious ruins at Mohenjodaro, the plains of Sind and the Punjab, the Khyber Pass, and his home town of Lahore. Imran’s amusing anecdotes and acute observations provide a unique insight into the richly varied life of Pakistan’s past and present; a life vividly portrayed by the superb colour photographs of Mike Goldwater. The result is a sumptuous personal view of Pakistan seen through the eyes of one of its most illustrious countrymen.

    This text is highly regarded because of its engaging and understandable introduction to statistics. The author's commitment to providing student-friendly guidance through the material and giving students opportunities to apply their newly learned skills in a real-world context has made Elementary Statistics the #1 best-seller in the market.

    R is packed with powerful programming capabilities, but learning to use R in the real world can be overwhelming for even the most seasoned statisticians. This easy-to-follow guide explains how to use R for data processing and statistical analysis, and then, shows you how to present your data using compelling and informative graphics. You'll gain practical experience using R in a variety of settings and delve deeper into R's feature-rich toolset.Includes tips for the initial installation of RDemonstrates how to easily perform calculations on vectors, arrays, and lists of dataShows how to effectively visualize data using R's powerful graphics packagesGives pointers on how to find, install, and use add-on packages created by the R communityProvides tips on getting additional help from R mailing lists and websitesWhether you're just starting out with statistical analysis or are a procedural programming pro, "R For Dummies" is the book you need to get the most out of R.

    Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions.Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more.Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.

    By the mid-1990s the old school grizzled traders had been replaced by a new breed of quantitative analysts, applying mathematics to the "art" of trading and making of it a science. A similar phenomenon is happening in poker. The grizzled "road gamblers" are being replaced by a new generation of players who have challenged many of the assumptions that underlie traditional approaches to the game. One of the most important features of this new approach is a reliance on quantitative analysis and the application of mathematics to the game. This book provides an introduction to quantitative techniques as applied to poker and to a branch of mathematics that is particularly applicable to poker, game theory, in a manner that makes seemingly difficult topics accessible to players without a strong mathematical background.

    

    Hunanyan, the #1 bestselling author of Black Book of Poems, comes his highly-anticipated second collection of poetry.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Indeed, numbers are part of every discipline in the sciences and the arts.With 350 illustrations, including diagrams, photographs and computer imagery, the book chronicles the centuries-long search for the meaning of numbers by famous and lesser-known mathematicians, and explains the puzzling aspects of the mathematical world. Topics include:The earliest ideas of numbers and counting Patterns, logic, calculating Natural, perfect, amicable and prime numbers Numerology, the power of numbers, superstition The computer, the Enigma Code Infinity, the speed of light, relativity Complex numbers The Big Bang and Chaos theories The Philosopher's Stone. The Book of Numbers shows enthusiastically that numbers are neither boring nor dull but rather involve intriguing connections, rivalries, secret documents and even mysterious deaths.