Dealing with measure theory and Lebesque integration, this is an introductory graduate text.

     Using case examples of both good and bad student practice, the handbook takes students through each step of the dissertation process, from their initial research proposal to the final submission. The author uses clear illustrations of what students need to do - or not do - to reach their potential, helping them to avoid the most common pitfalls. This essential handbook covers: Producing focused and relevant research objectives Writing your literature review Citing your sources correctly Clearly explaining your use of research methods Writing up your findings Summarizing your work by linking your conclusions to your initial proposal Understanding marking schemes Aimed primarily at Master's students or students on short postgraduate courses in business, humanities and the social sciences, this book is also key reading for supervisors and undergraduates considering postgraduate study.

    Numerous examples are provided to reinforce the concepts and relevant case studies illustrate the concepts and mechanisms described.

    With its comprehensive, succinct, and applied coverage, the text has proven its ability to capture students' interest while introducing them to the issues, forces, and outcomes that make us who we are. Robert V. Kail's expertise in childhood and adolescence, combined with John C. Cavanaugh's extensive research in gerontology, result in a book with a rich description of all life-span stages and important topics. A modified chronological approach traces development in sequential order from conception through late life, while also dedicating several chapters to key topical issues. This organization also allows the book to be relatively briefer than other texts?a benefit given the enormous amount of information covered in the course. Benefits: NEW! Up-to-date findings and references introduce students to the perspectives of those who are currently shaping the field and those who pioneered it. New examples include a greater number of diversity examples to appeal to the broadest possible range of students: a diversity theme index is in the back of the book. Real People: Applying Human Development boxes illustrate how a development issue is manifested in the life of a real person. Examples include "Tell Me About a Girl That You Like A Lot and "Still Flying at 91." NEW! Read about the latest research insights?Current findings and references introduce you to the perspectives of those who are currently shaping the field and those who pioneered it. NEW! Study smarter?Learning Objectives (listed at the beginning of each major section and repeated as subheads throughout the section) help you study more efficiently by focusing your attention on important upcoming topics. NEW! Build critical thinking skills painlessly?Wikipedia, YouTube, Facebook, texting, and other current topics make the book's Think About It questio

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    Particularly suitable for students of secondary-school level, it is also a handy dictionary for the home and office. It covers all the words you need for everyday use, and has excellent coverage of curriculum vocabulary. For the new edition the definitions are clearer than ever before and there is lots of help with those aspects of the language (such as spelling, pronunciation, and usage) which cause most difficulties.In particular, there are hundreds of new spelling notes to help with tricky words that are commonly misspelled, extra usage notes giving advice on good English, and more help with pronunciations of difficult words. A new open design ensures that this dictionary is even more accessible and easier to use than ever before.

    While the mathematics is there, the effort is not all concentrated on proofs. Strang's emphasis is on understanding. He explains concepts, rather than deduces. This book is written in an informal and personal style and teaches real mathematics. The gears change in Chapter 2 as students reach the introduction of vector spaces. Throughout the book, the theory is motivated and reinforced by genuine applications, allowing pure mathematicians to teach applied mathematics.

    Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problemsEach chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer supportThe authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data miningMore advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data miningCovers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis

    It also discusses 'mixed methods research', that is, the various combinations of qualitative and quantitative methodologies.

    Written by authors who are highly regarded in the field, the text provides sound methodological development. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems. Statistics for Business and Economics, 9e offers proven accuracy that has led instructors to adopt it simply for its superior examples and exercises alone.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for shastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.This book is being published in two volumes. This second volume develops shastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time.Masters level students and researchers in mathematical finance and financial engineering will find this book useful.Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

    This edition retains the scope and emphasis that have made the book very successful while adding over twenty new numerical examples and over 550 new end-of-chapter problems.

    Robert Kaplan and Dennis Saccuzzo provide students with a current analysis of the most widely used psychological tests in schools, professional training programs, business, industry, the military, and clinical settings. The authors offer a clear picture of how psychological tests are constructed, how they are used, and how an understanding of them can make a difference in their careers and everyday lives. Comprehensive and accurate, yet interesting and personally relevant, this book gets and keeps students' attention through the use of informal discussions and real-life examples.

    Jon C. Thompson presents the latest data in thoroughly updated diagnostic and treatment algorithms for all conditions while preserving the popular at-a-glance table format from the previous edition. You'll get even more art from the Netter Collection as well as new radiologic images that visually demonstrate the key clinical correlations and applications of anatomical imaging. For a fast, memorable review of orthopaedic anatomy, this is a must-have.Maintains the popular at-a-glance table format that makes finding essential information quick and convenient.Contains useful clinical information on disorders, trauma, history, physical exam, radiology, surgical approaches, and minor procedures in every chapter.Lists key information on bones, joints, muscles, and nerves in tables correlate to each Netter image.Highlights key material in different colors-pearls in green and warnings in red-for easy reference. Features both plain film and advanced radiographic (CT and MRI) images, along with cross-sectional anatomic plates for an even more thorough visual representation of the material.Includes additional common surgical approaches to give you a broader understanding of techniques.Incorporates reorganized Complicated Arthology tables for large joints, such as the shoulder, knee, and hip, for increased clarity and to incorporate new artwork and additional clinical correlations.Reflects new data and current diagnostic and treatment techniques through updates to the Disorders and Fractures sections and the Physical Exam and Anatomic tables in each chapter.Presents the very latest developments in the field through thoroughly updated diagnostic and treatment algorithms for all clinical conditions.