This book provides an applications-oriented introduction to multivariate data analysis for the non-statistician, by focusing on the fundamental concepts that affect the use of specific techniques.

    This text is highly regarded because of its engaging and understandable introduction to statistics. The author's commitment to providing student-friendly guidance through the material and giving students opportunities to apply their newly learned skills in a real-world context has made Elementary Statistics the #1 best-seller in the market.

    The book is a complete revision of the commands section of Sobell's Practical Guide to Linux - a proven best-seller. The book is Linux distribution and release agnostic. It will appeal to users of ALL Linux distributions. Superior examples make this book the the best option on the market! System administrators, software developers, quality assurance engineers and others working on a Linux system need to work from the command line in order to be effective. Linux is famous for its huge number of command line utility programs, and the programs themselves are famous for their large numbers of options, switches, and configuration files. But the truth is that users will only use a limited (but still significant) number of these utilities on a recurring basis, and then only with a subset of the most important and useful options, switches and configuration files. This book cuts through all the noise and shows them which utilities are most useful, and which options most important. And it contains examples, lot's and lot's of examples. programmability. Utilities are designed, by default, to work wtih other utilities within shell programs as a way of automating system tasks. This book contains a superb introduction to Linux shell programming. And since shell programmers need to write their programs in text editors, this book covers the two most popular ones: vi and emacs.

    In a few years, it's expected to be found inside millions of cell phones and other mobile devices, making Android a major platform for application developers. That could be your own program running on all those devices.Getting started developing with Android is easy. You don't even need access to an Android phone, just a computer where you can install the Android SDK and the phone emulator that comes with it. Within minutes, "Hello, Android" will get you creating your first working application: Android's version of "Hello, World."From there, you'll build up a more substantial example: an Android Sudoku game. By gradually adding features to the game throughout the course of the book, you'll learn about many aspects of Android programming including user interfaces, multimedia, and the Android life cycle.If you're a busy developer who'd rather be coding than reading about coding, this book is for you. To help you find what you need to know fast, each chapter ends with "Fast forward" section. These sections provide guidance for where you should go next when you need to read the book out of order.

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    This book is indispensable for anyone who is serious about using jQuery for non-trivial applications." -- Raffaele Cecco, longtime developer of video games, including Cybernoid, Exolon, and StormlordjQuery is the "write less, do more" JavaScript library. Its powerful features and ease of use have made it the most popular client-side JavaScript framework for the Web. This book is jQuery's trusty companion: the definitive "read less, learn more" guide to the library.jQuery Pocket Reference explains everything you need to know about jQuery, completely and comprehensively. You'll learn how to:Select and manipulate document elementsAlter document structureHandle and trigger eventsCreate visual effects and animationsScript HTTP with Ajax utilitiesUse jQuery's selectors and selection methods, utilities, plugins and moreThe 25-page quick reference summarizes the library, listing all jQuery methods and functions, with signatures and descriptions.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    HOW RISKY IS IT, REALLY?International risk expert David Ropeik takes an in-depth look at our perceptions of risk and explains the hidden factors that make us unnecessarily afraid of relatively small threats and not afraid enough of some really big ones. This read is a comprehensive, accessible, and entertaining mixture of what's been discovered about how and why we fear — too much or too little. It brings into focus the danger of The Perception Gap: when our fears don't match the facts, and we make choices that create additional risks.This book will not decide for you what is really risky and what isn't. That's up to you. HOW RISKY IS IT, REALLY? will tell you how you make those decisions. Understanding how we perceive risk is the first step toward making wiser and healthier choices for ourselves as individuals and for society as a whole.TEST YOUR OWN "RISK RESPONSE" IN DOZENS OF SELF-QUIZZES!

    In addition to giving a strong foundation in the language itself, Lubanovic shows how to use it for a range of applications in business, science, and the arts, drawing on the rich collection of open source packages developed by Python fans.It's impressive how many commercial and production-critical programs are written now in Python. Developed to be easy to read and maintain, it has proven a boon to anyone who wants applications that are quick to write but robust and able to remain in production for the long haul.This book focuses on the current version of Python, 3.x, while including sidebars about important differences with 2.x for readers who may have to deal with programs in that version.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    Built for your brain, this book covers C# 3.0 and Visual Studio 2008, and teaches everything from language fundamentals to advanced topics including garbage collection, extension methods, and double-buffered animation. You'll also master C#'s hottest and newest syntax, LINQ, for querying SQL databases, .NET collections, and XML documents. By the time you're through, you'll be a proficient C# programmer, designing and coding large-scale applications. Every few chapters you will come across a lab that lets you apply what you've learned up to that point. Each lab is designed to simulate a professional programming task, increasing in complexity until-at last-you build a working Invaders game, complete with shooting ships, aliens descending while firing, and an animated death sequence for unlucky starfighters. This remarkably engaging book will have you going from zero to 60 with C# in no time flat.

    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.

    It includes rewritten and clarified proofs and derivations, as well as new topics such as Arnoldi iteration, and domain decomposition methods.

    The book focuses on using SQL to find the story your data tells, with the popular open-source database PostgreSQL and the pgAdmin interface as its primary tools.You'll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from the U.S. Census and other federal and state government agencies. With exercises and real-world examples in each chapter, this book will teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently.You'll learn how to: •Create databases and related tables using your own data •Define the right data types for your information •Aggregate, sort, and filter data to find patterns •Use basic math and advanced statistical functions •Identify errors in data and clean them up •Import and export data using delimited text files •Write queries for geographic information systems (GIS) •Create advanced queries and automate tasks Learning SQL doesn't have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases. This book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.