It's not just a technical book or just a businessguide. Data is ubiquitous and it doesn't pay much attention toborders, so we've calibrated our coverage to follow it wherever itgoes.In the first edition of Big Data Now, the O'Reilly team tracked thebirth and early development of data tools and data science. Now, withthis second edition, we're seeing what happens when big data grows up:how it's being applied, where it's playing a role, and theconsequences -- good and bad alike -- of data's ascendance.We've organized the second edition of Big Data Now into five areas:Getting Up to Speed With Big Data -- Essential information on thestructures and definitions of big data.Big Data Tools, Techniques, and Strategies -- Expert guidance forturning big data theories into big data products.The Application of Big Data -- Examples of big data in action,including a look at the downside of data.What to Watch for in Big Data -- Thoughts on how big data will evolveand the role it will play across industries and domains.Big Data and Health Care -- A special section exploring thepossibilities that arise when data and health care come together.

    Never again will you order the Poisson Distribution in a French restaurant!This updated version features all new material.

    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 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

    From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.

    With laws getting stricter by the day and making it more and more difficult to properly protect your personal information, you need the most up-to-date information and tools available and that's what you will find in Incognito Toolkit! Don't let snoopers, investigators, and scammers look over your shoulder or track you while you work and play on the internet! Learn about the tools that will help you use the internet anonymously, privately, and securely to protect assets, avoid social stigmas, and make you safer. This book is full of information that large corporations, scammers, and nosy governments don't want you to find! You won't find a collection of techniques and creative methods like this anywhere else! Covered in Incognito Toolkit: - Making truly anonymous online purchases - Shortcomings of Bitcoin - Encrypting communications - Encryption for online file storage solutions - Locking down and monitoring your hardware - Browser Fingerprinting - Using TOR and VPNs - Creative Text and File Steganography Techniques - Critical Techniques for Publishing Anonymously - Cleaning photo and video metadata - Dealing with tracking cookies Updated December 4th, 2013 with new information about credit card skimmers, TOR hardware devices, and more! Scroll up and click the "Look Inside" feature on the top left hand side of the page!

    

    These sections together make an appropriate one-term advanced/graduate level course (mathematical prerequisites: vector analysis and simple partial-differential equations). The book is printed to make it easy for readers to identify these sections.• The remaining Track 2 material provides a wealth of advanced topics instructors can draw from to flesh out a two-term course, with Track 1 sections serving as prerequisites.

    This clear, concise look at the basic principles and concepts of genetics uses a human genetics perspective to discuss the methods and experiments upon which genetic principles are based, such as DNA replication.

    It invites both introductory and advanced students to appreciate the roots and limits of American exceptionalism, and to recognize the profound importance of current debates over the government's role in our everyday lives.

    In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

     But Drake’s exploits in his earlier years, though less well known, are even more remarkable. Born into a poor, obscure family, he worked his way rapidly up in the maritime world to his first captaincy. Before long, he was the most successful of all English pirates, admired by his countrymen, hated and feared by the Spanish. Queen Elizabeth and her ministers saw the potential in this rough-mannered but enterprising young man, and gave him their blessing for the first British venture into the Pacific Ocean. This success of this voyage, which lasted for three years, exceeded their wildest hopes. Not only did Drake come home with a vast treasure of captured gold, silver and jewels; he became the first man ever to circumnavigate the globe in a single mission, and bring most of his crew home alive and well. Soon after his triumphant return, Elizabeth knighted this newly rich adventurer, and gave her blessing to his acts of pillage. It was a gesture that made war with Spain inevitable. And Drake’s part in the coming war changed the course of world history. SIR FRANCIS DRAKE: THE QUEEN’S PIRATE tells the extraordinary story of Drake’s early years and his journey around the world on his famous ship, the Golden Hind.

    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.

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    Underlining the importance of critical thinking in all matters numerical, Best illustrates his points with examples of good and bad statistics about such contemporary concerns as school shootings, fatal hospital errors, bullying, teen suicides, deaths at the World Trade Center, college ratings, the risks of divorce, racial profiling, and fatalities caused by falling coconuts."More Damned Lies and Statistics" encourages all of us to think in a more sophisticated and skeptical manner about how statistics are used to promote causes, create fear, and advance particular points of view.