Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.

Discover how easy it is to design killer interfaces and responsive websites with the Bootstrap framework. This practical book gets you started building pages with Bootstrap’s HTML/CSS-based tools and design templates right away. You’ll also learn how to extend your app with interactive features, using its suite of jQuery plugins—often without writing a single line of code. Developed by Twitter and available free from GitHub, Bootstrap supports responsive design by dynamically adjusting your web page layout. With just a basic knowledge of HTML, CSS, and JavaScript, you can build apps that work equally well on desktop screens, smartphones, and tablets. This book shows you how. Become familiar with Bootstrap’s file structure, grid systems, and container layouts Learn HTML elements for typography, code, tables, forms, buttons, images, and icons Design interfaces and other web elements, such as navigation, breadcrumbs, and custom modal windows Use jQuery plugins for features such as revolving slideshows, tabbable interfaces, and dropdown menus Modify everything from column count to typography colors with the LESS stylesheet language

Explores the application of bootstrap to problems that place unusual demands on the method. The bootstrap method, introduced by Bradley Efron in 1973, is a nonparametric technique for inferring the distribution of a statistic derived from a sample. Most of the papers were presented at a special meeting sponsored by the Institute of Mathematical Statistics and the Interface Foundation in May, 1990.

This monograph addresses two quite different topics, each being able to shed light on the other. Firstly, it lays the foundation for a particular view of the bootstrap. Secondly, it gives an account of Edgeworth expansion. The first two chapters deal with the bootstrap and Edgeworth expansion respectively, while chapters 3 and 4 bring these two themes together, using Edgeworth expansion to explore and develop the properties of the bootstrap. The book is aimed at graduate level for those with some exposure to the methods of theoretical statistics. However, technical details are delayed until the last chapter such that mathematically able readers without knowledge of the rigorous theory of probability will have no trouble understanding most of the book.

Disk contains the library functions and documentation for use with Splus for Windows.

A queer time-travel adventure from the award-winning author of Loner