rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Resampling Methods
    sub title: A Practical Guide to Data Analysis
  name:
    name part: Good, Phillip I.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2006
    edition: Third Edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XX, 218 p. online resource.
  abstract: "…the author has packaged an excellent and modern set of topics around the development and use of quantitative models.... If you need to learn about resampling, this book would be a good place to start." —Technometrics (Review of the Second Edition) This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, the book provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. Topics and Features * Practical presentation covers both the bootstrap and permutations along with the program code necessary to put them to work. * Includes a systematic guide to selecting the correct procedure for a particular application. * Detailed coverage of classification, estimation, experimental design, hypothesis testing, and modeling. * Suitable for both classroom use and individual self-study. New to the Third Edition * Procedures are grouped by application; a prefatory chapter guides readers to the appropriate reading matter. * Program listings and screen shots now accompany each resampling procedure: Whether one programs in C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-PLUS, Stata, or StatXact, readers will find the program listings and screen shots needed to put each resampling procedure into practice. * To simplify programming, code for readers to download and apply is posted at http://www.springeronline.com/0-8176-4386-9. * Notation has been simplified and, where possible, eliminated. * A glossary and answers to selected exercises are included. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, stu…
  table of contents: Software for Resampling -- Estimating Population Parameters -- Comparing Two Populations -- Choosing the Best Procedure -- Experimental Design and Analysis -- Categorical Data -- Multiple Variables and Multiple Hypotheses -- Model Building -- Decision Trees.
  note: by Phillip I. Good.
  subject:
    topic: Mathematics
  subject:
    topic: Mathematical analysis
  subject:
    topic: Analysis (Mathematics)
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Analysis
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Statistics, general
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  identifier: 9780817644444
  identifier: http://dx.doi.org/10.1007/0-8176-4444-X
  record info:
    record creation date: 100301
    record change date: 20151204144343.0
    record identifier: 978-0-8176-4444-4