It follows standards-based principles, but also teaches readers ways around problems they are likely to face using (X)HTML.While XHTML is the "current" standard, the book still covers HTML because many people do not yet understand that XHTML is the official successor to HTML, and many readers will still stick with HTML for backward compatibility and simpler/informal Web pages that don't require XHTML compliance.The book teaches basic principles of usability and accessibility along the way, to get users into the mode of developing Web pages that will be available to as many viewers as possible from the start. The book also covers the most commonly used programming/scripting language -- JavaScript -- and provides readers with a roadmap of other Web technologies to learn after mastering this book to add more functionality to their sites.

    The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.About the TechnologyR is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.About the BookR in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and non-normal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's InsidePractical data analysis, step by stepInterfacing R with other softwareUsing R to visualize dataOver 130 graphsEight reference appendixes================================Table of ContentsPart I Getting startedIntroduction to RCreating a datasetGetting started with graphsBasic data managementAdvanced data managementPart II Basic methodsBasic graphsBasic statisticsPart III Intermediate methodsRegressionAnalysis of variancePower analysisIntermediate graphsRe-sampling statistics and bootstrappingPart IV Advanced methodsGeneralized linear modelsPrincipal components and factor analysisAdvanced methods for missing dataAdvanced graphics

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    

    A CD-ROM with demos, code, compiler, executables, and MATLAB examples has been added to the book. Simplicity and an easy narration style are the hallmarks of the book, which have made its previous seven editions immensely successful. Today s C programmer (still the language of choice in science, engineering, game programming and for handheld devices) has to master the complexities of the language and contend with its usage in environments like Windows, Linux, and for the Internet. This book covers these three aspects of C programming and doesn t assume any programming background. It begins with the basics and steadily builds the pace, so the reader finds it easy to handle more complicated topics later. This popular author has crafted hundreds of excellent programming examples and exercises for every aspect of C programming. ++++Features +Self-study format provides hundreds of step by step examples and exercises + Assumes no programming knowledge; starts with the basics and progresses to more difficult topics +Includes a CD-ROM with demos, code, compiler, executables, and MATLAB examples +Covers the latest programming techniques for Windows, Linux, and the Internet ++++++Selected Topics Traditional C Programming; Pointers; Complete Build Process; Low-level File I/O; Structures, Unions, Bit-fields; Bitwise Operators. C Under Linux; Signals and Signal Handling; Blocking of Signals; Event Driven Programming; Process; PIDs; Zombies; GNOME Programming Using GTK Library. C Under Windows. Windows Programming Model; Windows Messaging Architecture; Mouse Programming; GDI. Internet Programming. CP/ IP model; Windsock Library; Building Time Clients; Whois and HTTP Clients; Sending & Receiving emails

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    

    

    It's all muscle and no fluff. Discover how the experts tackle Windows 7--and challenge yourself to new levels of mastery! Compare features and capabilities in each edition of Windows 7.Configure and customize your system with advanced setup options.Manage files, folders, and media libraries.Set up a wired or wireless network and manage shared resources.Administer accounts, passwords, and logons--and help control access to resources.Configure Internet Explorer 8 settings and security zones.Master security essentials to help protect against viruses, worms, and spyware.Troubleshoot errors and fine-tune performance.Automate routine maintenance with scripts and other tools. CD includes: Fully searchable eBookDownloadable gadgets and other tools for customizing Windows 7Insights direct from the product team on the official Windows 7 blogLinks to the latest security updates and products, demos, blogs, and user communities For customers who purchase an ebook version of this title, instructions for downloading the CD files can be found in the ebook.

    Designed for experienced developers ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the Microsoft Specialist level.Focus on the expertise measured by these objectives:Design the application architectureDesign the user experienceDevelop the user experienceTroubleshoot and debug web applicationsDesign and implement securityThis Microsoft Exam Ref:Organizes its coverage by exam objectives.Features strategic, what-if scenarios to challenge you.Includes a 15% exam discount from Microsoft. (Limited time offer)

    Each mini-chapter adds one feature to the ray tracer, and by the end the reader can produce the image on the book cover. Details of basic ray tracing code architecture and C++ classes are given.