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

    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 covers social and interpersonal skills, as well as the underlying cultural assumptions and values of the Russian people.

    Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of core data areas: Data issues -- The opportunities and ambiguities of the data space are evident in discussions around privacy, the implications of data-centric industries, and the debate about the phrase “data science” itself. The application of data: products and processes – A “data product” can emerge from virtually any domain, including everything from data startups to established enterprises to media/journalism to education and research. Data science and data tools -- The tools and technologies that drive data science are of course essential to this space, but the varied techniques being applied are also key to understanding the big data arena.The business of data – Take a closer look at the actions connected to data -- the finding, organizing, and analyzing that provide organizations of all sizes with the information they need to compete.

    The author was—at first.When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind.Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold.This book will help you understand:• Why big data is important to you and your organization• What technology you need to manage it• How big data could change your job, your company, and your industry• How to hire, rent, or develop the kinds of people who make big data work• The key success factors in implementing any big data project• How big data is leading to a new approach to managing analyticsWith dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.

    It uses a combination of marketing, statistical, and psychological research to explain why and, more importantly, how, companies should adapt marketing strategies such as blogging, social media, email marketing, and webinars to achieve maximium results.The book contradicts what the author calls the "unicorns and rainbows" strategy that simply encourages companies to love their customers and hug their followers. Instead, the book offers more substantial, proven tactics and tips gathered through scientific research and techniques.Lists what time of day and what day of the week the most retweets occur Explains why weekends are best for Facebook sharing, which blog posts lead to comments, why early mornings are best for emails, and how to blog to acquire links Describes how to avoid crowding your content The Science of Marketing provides the research and tools to help you make a stronger impact in the digital marketing space.

    The author explains, and illustrates, basic concepts such as the co-operative principle, deixis, and speech acts, providing a clear, concise foundation for further study.

    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

    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.

    "Fake Science 101" is here to tackle those questions that are too tough to really answer. Like why is the sky blue? Where did the dinosaurs go? And what's with Einstein's hair?If you love Fake Science on the World Wide Web, you will love it even more on paper.* This cutting-edge volume shares the freshest discoveries to date made by the Fake Science lab--and completely ignores the sneers from the scientific community over its lack of research. "Fake Science 101" is your go-to textbook for when the facts are just too confusing.*Unless you are a tree.

    It discusses the structure and content of the human word-store or mental lexicon with particular reference to the spoken language of native English speakers.

    This problem has deep philosophical implications: If languages are all the same, it implies a fundamental commonality--and thus mutual intelligibility--of human thought.We are now on the verge of solving this problem. Using a twenty-year-old theory proposed by the world's greatest living linguist, Noam Chomsky, researchers have found that the similarities among languages are more profound than the differences. Languages whose grammars seem completely incompatible may in fact be structurally almost identical, except for a difference in one simple rule. The discovery of these rules and how they may vary promises to yield a linguistic equivalent of the Periodic Table of the Elements: a single framework by which we can understand the fundamental structure of all human language. This is a landmark breakthrough both within linguistics, which will herewith finally become a full-fledged science, and in our understanding of the human mind.

    Keeping themorganized can be a challenge, but an organized classroom is essential and allows students and the teacher to fully focus on learning by eliminating distractions. Organized Teacher, Happy Classroom provides practical, proven methods for maintaining an organized classroom throughout the entire school year.Inside you’ll find:• Strategies for managing students’ papers, curriculum material, and essential paperwork• Time management tips to maximize your instruction time and lesson planning• Organizing systems you can teach your students to improve self reliance andaccountability• Checklists for starting and ending the year well organized• Helpful forms and templates you can use in your classroom• Plans for arranging a classroom that promotes positive student participation• Support to simplify your classroom• Efficient storage solutions for all teacher and student materialsWhether you teach primary, intermediate, middle school or high school, this bookwill help you organize your time, paperwork, and classroom spaces.

    As a result, many students talk about college in ways that cause them to overlook some of their most important learning opportunities. Becoming a Learner asks students to carefully reconsider conventional common sense about college and learning, and invites them to consider a new conversation about college and learning that focuses on who they are becoming and their ability to learn.

    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.