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"Mathematical statistics Graphic methods."
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Graphic Discovery
Good graphs make complex problems clear. From the weather forecast to the Dow Jones average, graphs are so ubiquitous today that it is hard to imagine a world without them. Yet they are a modern invention. This book is the first to comprehensively plot humankind's fascinating efforts to visualize data, from a key seventeenth-century precursor--England's plague-driven initiative to register vital statistics--right up to the latest advances. In a highly readable, richly illustrated story of invention and inventor that mixes science and politics, intrigue and scandal, revolution and shopping, Howard Wainer validates Thoreau's observation that circumstantial evidence can be quite convincing, as when you find a trout in the milk. The story really begins with the eighteenth-century origins of the art, logic, and methods of data display, which emerged, full-grown, in William Playfair's landmark 1786 trade atlas of England and Wales. The remarkable Scot singlehandedly popularized the atheoretical plotting of data to reveal suggestive patterns--an achievement that foretold the graphic explosion of the nineteenth century, with atlases published across the observational sciences as the language of science moved from words to pictures. Next come succinct chapters illustrating the uses and abuses of this marvelous invention more recently, from a murder trial in Connecticut to the Vietnam War's effect on college admissions. Finally Wainer examines the great twentieth-century polymath John Wilder Tukey's vision of future graphic displays and the resultant methods--methods poised to help us make sense of the torrent of data in our information-laden world.
eBook
Making bar graphs
Guides readers through the different parts of a bar graph, including its title, labels, and scale.
Book
Graphical models : representations for learning, reasoning and data mining
Graphical models are of increasing importance in applied statistics, and in particular in data mining. Providing a self-contained introduction and overview to learning relational, probabilistic, and possibilistic networks from data, this second edition of Graphical Models is thoroughly updated to include the latest research in this burgeoning field, including a new chapter on visualization. The text provides graduate students, and researchers with all the necessary background material, including modelling under uncertainty, decomposition of distributions, graphical representation of distributions, and applications relating to graphical models and problems for further research.
eBook
Making circle graphs
Understanding circle graphs, also known as pie charts, is an important math skill. This book investigates the topic using engaging and accessible examples such as sports. Readers examine several circle graphs closely and are guided step-by-step through the process of making their own. A bright design, clear text, and a self-evaluation quiz make this a valuable resource for any classroom. Step-by-Step Instructions, Quiz, Glossary, For Further Information Section, Index.
Book
Visualizing Data Patterns with Micromaps
This full-color book explores the design variations and applications of micromaps, which link statistical information to an organized set of small maps. It illustrates the three main types of micromaps (linked, conditioned, and comparative) and summarizes the cognitive research and statistical thinking behind these designs. The book then explains the specific design elements and applications of each of the main micromap designs. To compare and contrast their purposes, limitations, and strengths, the final chapter applies all three of these techniques to the same demographic data for Louisiana before and after Hurricanes Katrina and Rita. Many supplementary resources are available on the book's website.
eBook
Programming Graphical User Interfaces in R
Focusing on graphic user interfaces (GUIs) within the R language, this book shows programmers and users how to develop their own GUIs, enabling them to interface with other languages. The text opens the possibilities of R's huge and growing set of statistical methods. The authors cover four different packages for writing GUIs: gWidgets, RGtk2, Qt, and Tcl Tk. Supported by a package in CRAN that contains all of the code along with additional examples, the text is filled with numerous examples ranging from the very simple to detailed illustrations of how to code actual interfaces.
eBook
Probabilistic Integration
A research frontier has emerged in scientific computation, wherein discretisation error is regarded as a source of epistemic uncertainty that can be modelled. This raises several statistical challenges, including the design of statistical methods that enable the coherent propagation of probabilities through a (possibly deterministic) computational work-flow, in order to assess the impact of discretisation error on the computer output. This paper examines the case for probabilistic numerical methods in routine statistical computation. Our focus is on numerical integration, where a probabilistic integrator is equipped with a full distribution over its output that reflects the fact that the integrand has been discretised. Our main technical contribution is to establish, for the first time, rates of posterior contraction for one such method. Several substantial applications are provided for illustration and critical evaluation, including examples from statistical modelling, computer graphics and a computer model for an oil reservoir.
Journal Article