It introduces the analysis of the key elements of language--sounds, words, structures and meanings, and provides a solid foundation in all of the essential topics. The third edition has been extensively revised to include new sections on important contemporary issues in language study, including language and culture, African American English, sign language, and slang. A comprehensive glossary provides useful explanations of technical terms, and each chapter contains a range of new study questions and research tasks, with suggested answers.

    In Dataclysm, Christian Rudder uses it to show us who we truly are.   For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.   In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.   Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

    John Snow. It's the summer of 1854, and London is just emerging as one of the first modern cities in the world. But lacking the infrastructure—garbage removal, clean water, sewers—necessary to support its rapidly expanding population, the city has become the perfect breeding ground for a terrifying disease no one knows how to cure. As the cholera outbreak takes hold, a physician and a local curate are spurred to action—and ultimately solve the most pressing medical riddle of their time. In a triumph of multidisciplinary thinking, Johnson illuminates the intertwined histories and inter-connectedness of the spread of disease, contagion theory, the rise of cities, and the nature of scientific inquiry, offering both a riveting history and a powerful explanation of how it has shaped the world we live in.

    While this version features an older Dummies cover and design, the content is the same as the new release and should not be considered a different product. The fun and easy way to get up to speed on the basic concepts of physics For high school and undergraduate students alike, physics classes are recommended or required courses for a wide variety of majors, and continue to be a challenging and often confusing course.Physics I For Dummies tracks specifically to an introductory course and, keeping with the traditionally easy-to-follow Dummies style, teaches you the basic principles and formulas in a clear and concise manner, proving that you don't have to be Einstein to understand physics!Explains the basic principles in a simple, clear, and entertaining fashion New edition includes updated examples and explanations, as well as the newest discoveries in the field Contains the newest teaching techniques If just thinking about the laws of physics makes your head spin, this hands-on, friendly guide gets you out of the black hole and sheds light on this often-intimidating subject.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    This book provides the first complete identification guides to the birds of this teeming tropical paradise. It gives descriptions of 820 regional species, illustrated in 88 specially commissioned color plates accompanied by notes detailing distinctive features and habitats. Entries cover nomenclature, plumage, markings, voice, global range, distribution and regional status, habits, and diet. The main text gives practical information on where to find many exotic species, citing major birdwatching locations. Introductory chapters discuss habitats, climate, land-use, and conservation concerns. Professional ornithologists and amateur bird watchers alike will find this the indispensable bird guide for eastern Malaysia and western Indonesia for many years to come. It is also an unrivalled source of information for casual travellers and ecotourists.

     Social Welfare Policy; 2008 Election; Proposition 8; Economic issues. Social work and social welfare practitioners and students interested in enhancing their understanding and analysis of social welfare policy.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    They influence virtually all of the growing individual's characteristics, from determining its sex to controlling the numbers of toes and fingers to shaping intricate details of brain structure.Scientific research over the last 50 years has revealed that this hormonal control of development is vulnerable to disruption by synthetic chemicals. Through a variety of mechanisms, hormone-disrupting chemicals (also known as endocrine disrupting chemicals or endocrine disruptors) interfere with the natural messages and alter the course of development, with potential effects on virtually all aspects of bodily function.Our Stolen Future explores the scientific discovery of endocrine disruption. The investigation begins with wildlife, as it was in animals that the first hints of widespread endocrine disruption appeared. The book then examines a series of experiments examining endocrine disruption of animals in the laboratory which show conclusively that fetal exposure to endocrine disrupting chemicals can wreak life-long damage. These experiments also reveal some of the biological processes by which these chemicals have their effects, and that endocrine disruption effects can be caused by exposure to infinitesimally small amounts of contaminant. Moving from animals to people, Our Stolen Future summarizes a series of well-studied examples where people have been affected by endocrine disrupting chemicals, most notably the synthetic hormone dietheylstilbestrol (DES), to which several million women were exposed through misguided medical attempts to manage difficult pregnancies in the 1950s, '60s and '70s.Our Stolen Future then asks a broader, more difficult and more controversial set of questions. Given what is known from wildlife and laboratory studies, and from examples of well-studied human exposure, and given that exposure to endocrine disrupting chemicals in the real world is widespread at levels comparable to those sufficient to cause animal harm, what effects should health scientists be looking for in people in general? Effects to be expected include declines in fertility and other impacts on the reproductive system of both men and women, impairments in disease resistance, and erosions in intelligence.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    This streamlined book is an excellent review for the larger text and an ideal primary text for health professions courses with brief coverage of anatomy.This edition features new full-color surface anatomy photographs and new diagnostic images. A new design makes the book visually appealing and easier to navigate.Accompanying the book is an Online Student Resource Center, which includes interactive clinical cases, USMLE-style review questions, and more.

    For each body system, broad coverage of anatomy, physiology, pathology, diagnostic procedures, treatment procedures, and pharmacology is provided. The author emphasizes both terms built from Latin and Greek word parts, and modern English terms, helping students develop a full working word part vocabulary they can use to interpret any new term. This edition contains many new terms, and has been reorganized for more efficient learning. To eliminate confusion, Word Building tables have been removed from each chapter and the terms have been distributed throughout the pathology, diagnostic procedure, and treatment procedure tables, where they are more immediately relevant to students. Note: This ISBN is just the standalone book, if the customer wants the book/access card order the ISBN below; 133962032 / 9780133962031 Medical Terminology: A Living Language PLUS MyMedicalTerminologyLab with Pearson etext -- Access Card Package Package consists of: 0132843471 / 9780132843478 Medical Terminology: A Living Language 0133936236 / 9780133936230 MyMedicalTerminologyLab with Pearson etext - Access Card - Medical Terminology A Living Language

    It is designed as a reference for students in the physical sciences and engineering.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    This book is the most engaging, focused and applied HRM text on the market.