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Mathematical statistics; Data processing

Most popular at the top

  • Software for Data Analysisby John Chambers

    Springer New York 2008; US$ 129.00

    This is the only advanced programming book on R, the enormously successful open-source system based on the S language. It guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages. more...

  • Lean Six Sigma Using SigmaXL and Minitabby Issa Bass; Barbara Lawton

    McGraw-Hill Education 2009; US$ 32.00

    Effectively Execute Lean Six Sigma Projects using SigmaXL and Minitab Written by a Six Sigma Master Black Belt and a Ph.D., this practical guide to Lean Six Sigma project execution follows the DMAIC (Define, Measure, Analyze, Improve, and Control) roadmap. The many real-world examples used in the book offer in-depth theoretical analyses and are... more...

  • LISP-STATby Luke Tierney

    Wiley 2009; US$ 198.00

    Written for the professional statistician or graduate statistics student, the primary objective of this book is to describe a system, based on the LISP language, for statistical computing and dynamic graphics to show how it can be used as an effective platform for a wide range of statistical computing tasks ranging from basic calculations to customizing... more...

  • Medical and Care Compunetics 6by S. Benton; B. Blobel; L. Bos

    IOS Press 2010; US$ 167.00

    Medical and care compunetics is the field which deals with the social, societal and ethical implications of computing and networking in relation to health care. This book presents proceedings from the seventh annual conference of the International Council on Medical and Care Compunetics (ICMCC);the focus for knowledge exchange in this subject. ICMCC... more...

  • Proceedings of COMPSTAT'2010by Yves Lechevallier; Gilbert Saporta

    Physica-Verlag HD 2010; US$ 259.00

    Proceedings of the 19th international symposium on computational statistics, held in Paris august 22-27, 2010.Together with 3 keynote talks, there were 14 invited sessions and more than 100 peer-reviewed contributed communications. more...

  • Visualize Thisby Nathan Yau

    Wiley 2011; US$ 39.99

    Practical data design tips from a data visualization expert of the modern age Data doesn?t decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn?t it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear,... more...

  • Think Statsby Allen B. Downey

    O'Reilly Media 2011; US$ 23.99

    If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. You'll work with a case study throughout the book to help you learn the entire... more...

  • Beginning Rby Mark Gardener

    Wiley 2012; US$ 34.99

    Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and... more...

  • Theory and Applications of Gaussian Quadrature Methodsby Narayan Kovvali

    Morgan & Claypool Publishers 2011; US$ 35.00

    Gaussian quadrature is a powerful technique for numerical integration that falls under the broad category of spectral methods. The purpose of this work is to provide an introduction to the theory and practice of Gaussian quadrature. We study the approximation theory of trigonometric and orthogonal polynomials and related functions and examine the analytical... more...

  • Behavioral Research Data Analysis with Rby Yuelin Li; Jonathan Baron

    Springer New York 2011; US$ 59.95

    This book is written for behavioral scientists who want to add the R programming language and software environment to their arsenal of statistical tools. The authors offer practical advice on widely-used statistical methods, using notes and annotated examples. more...