This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo MCMC. Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

    Hamilton was reshaping the image of the vampire with her own take on the vampire mythos in her Anita Blake, Vampire Hunter fantasy novel series. While Hamilton's work draws on traditional vampire and fairy lore, her interpretation of these subjects brought new dimensions to the genres, influencing the direction of urban fantasy over the past two decades.Reading Laurell K. Hamilton focuses upon Hamilton's two bestselling series, the Anita Blake, Vampire Hunter series and the Merry Gentry series. The volume is intended as a resource for leaders of book clubs or discussion groups, containing chapters that examine Hamilton's role in the current vampire literature craze, the themes and characters in her work, and responses to Hamilton on the Internet. The book also provides a brief overview of Hamilton's life.

    With a logical, body-systems organization and engaging terminology exercises throughout, it's your key to communicating confidently and effectively with other health care professionals.Systematic approach to terminology prepares you to recognize and define new words as you encounter them and build the medical vocabulary you'll need in the health care setting.Pronunciation key provides quick access to frequently referenced material.Complimentary and Alternative Medicine terms boxes highlight words and phrases associated with this increasingly popular discipline.Case studies encourage critical thinking and demonstrate how to apply the information you've learned.Terminology flash cards, included with every book, give you valuable review and self-assessment tools you can take anywhere for study on the go.Evolve resources enhance your learning and reinforcement opportunities with additional exercises, a Spanish/English glossary, and the Body Spectrum Electronic Anatomy Coloring Book.Medical Terminology Online, available at an additional charge, gives you access to a complete online course for the most advanced learning and understanding.New terms and abbreviations familiarize you with the latest terminology in use in health care.New images and illustrations visually acquaint you with pathologic information and procedures you'll encounter in the clinical setting.Enhanced chapter features highlight important concepts and provide guidance for more effective learning and study.CD references within the text direct you to expanded learning opportunities on the companion CD.More than 20 new medical records let you practice medical terminology using the forms you'll encounter in the clinical setting.New icons make it easy to distinguish a variety of helpful boxes and reference the material you need quickly.Answers to review exercises help you gauge your strengths and weaknesses and configure the most effective study plan for you.Website boxes refer you to valuable content you can access online for further learning.Revised pharmacy appendix helps you easily reference key pharmaceutical terms.The vastly updated companion CD provides fun alternatives for reinforcing what you've learned with new learning games, including Medical Millionaire and Termbusters.Enhanced audio companion, available on CD or as iTerms downloads for portable media players, helps you perfect your pronunciation skills and confidently use the terms you've learned in practice.

    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.

    The presentation is never awkward or dry, as it sometimes is in other "modern" textbooks; it is as unconventional as one has come to expect from the author. The book contains about 350 well placed and instructive problems, which cover a considerable part of the subject. All in all, this is an excellent work, of equally high value for both student and teacher." Zentralblatt f�r Mathematik

    In 2007, Janet Belsky's "Experiencing the Lifespan" was published to widespread instructor and student acclaim, ultimately winning the 2008 Textbook Excellence Award from the Text and Academic Authors Association. Now that breakthrough text returns in a rigorously updated edition that explores the lifespan by combining the latest research with a practicing psychologist's understanding of people, and a teacher's understanding of students and classroom dynamics. And again, all of this in the right number of pages to fit comfortably in a single term course.

    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

    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.

    The applications and computations in operations research are emphasized. Significantly revised, this text streamlines the coverage of the theory, applications, and computations of operations research. Numerical examples are effectively used to explain complex mathematical concepts. A separate chapter of fully analyzed applications aptly demonstrates the diverse use of OR. The popular commercial and tutorial software AMPL, Excel, Excel Solver, and Tora are used throughout the book to solve practical problems and to test theoretical concepts. New materials include Markov chains, TSP heuristics, new LP models, and a totally new simplex-based approach to LP sensitivity analysis.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    And yet, so much is still misunderstood about this chronic disorder. Mayo Clinic Guide to Fibromyalgia is an invaluable resource for understanding fibromyalgia and its debilitating symptoms.Those living with fibromyalgia know it is an invasive disorder, one that can cause overwhelming fatigue, joint stiffness, sleep problems, migraines, digestive problems, and troubles with memory and concentration, a symptom so common it is often referred to as “fibrofog.” While it's believed that humans have suffered from fibromyalgia for hundreds, even thousands, of years, a delay in medical research means many people living with fibromyalgia are still in the dark, confused by their symptoms and what causes the painful disorder. By drawing upon decades of advanced research in studying and treating fibromyalgia, Mayo Clinic Guide to Fibromyalgia combines anecdotes from real cases with expertise from Mayo Clinic’s rheumatology and chronic pain experts to provide an all-encompassing guide for understanding one of the most common chronic illnesses affecting Americans today. This book also offers reasonable, proven strategies—like worksheets to help readers craft a personalized daily plan—for managing common fibromyalgia symptoms, while serving as a comforting guide for those who may feel alone in their journey with fibromyalgia.  This book breaks down what fibromyalgia is—and isn’t—in 4 separate sections: ·       Section 1 introduces fibromyalgia, the history and modern discoveries of fibromyalgia research, as well as common myths and misconceptions associated with the condition ·       Section 2 outlines the different treatment options available to those who suffer from fibromyalgia, including prescription medications, therapies, and forms of integrative medicine ·       Section 3 offers helpful tips for managing—and improving—chronic pain through diet, exercise, sleep, and stress management ·       Finally, Section 4 explains how to find guidance and support from your family, friends, and physicians to help you live a life unhindered by fibromyalgia If you’re struggling to advance past your painful fibromyalgia symptoms, get the book Publisher’s Weekly described as “the first [book] a newly diagnosed patient should consult.”

    The book begins with an introduction to the language of statistics and then covers descriptive statistics and inferential statistics. Throughout, the author offers readers:- Difficulty Rating Index for each chapter′s material- Tips for doing and thinking about a statistical technique- Top tens for everything from the best ways to create a graph to the most effective techniques for data collection- Steps that break techniques down into a clear sequence of procedures- SPSS tips for executing each major statistical technique- Practice exercises at the end of each chapter, followed by worked out solutions.The book concludes with a statistical software sampler and a description of the best Internet sites for statistical information and data resources. Readers also have access to a website for downloading data that they can use to practice additional exercises from the book. Students and researchers will appreciate the book′s unhurried pace and thorough, friendly presentation.

    Highlights of the book include realistic problems and examples from a wide range of application areas. New to this edition are: much sharper pedagogy; an increase in the number of examples; more thorough development of the concepts; a greater range of homework problems; a greater number and variety of worked out examples; expanded coverage of dynamics modelling and Laplace transform topics; and integration of MATLAB, including many examples that are formatted in MATLAB.