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: Probability with Applications in Engineering, Science, and Technology
  name:
    name part: Carlton, Matthew A.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Devore, Jay L.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXXII, 776 p. 209 illus., 178 illus. in color. online resource.
  abstract: This book provides a contemporary and lively postcalculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. A one-term course would cover material in the core chapters (1-4), hopefully supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8). The last chapter is specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise. Alternatively, there is certainly enough material for those lucky enough to be teaching or taking a year-long course. Most of the core will be accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the later, more advanced chapters. One unique feature of this book is the inclusion of sections that illustrate the importance of software for carrying out simulations when answers to questions cannot be obtained analytically; R and Matlab code are provided so that students can create their own simulations. Another feature that sets this book apart is the Introduction, which addresses the question “Why study probability?” by surveying selected examples from recent journal articles and discussing some classic problems whose solutions run counter to intuition. The book contains about 1100 exercises, ranging from straightforward to reasonably challenging; roughly 700 of these appear in the first four chapters. The book’s preface provides more information about our purpose, c…
  table of contents: Probability -- Discrete Random Variables and Probability Distributions -- Continuous Random Variables and Probability Distributions -- Joint probability distributions and their applications -- The Basics of Statistical Inference -- Markov chains -- Random processes -- Introduction to signal processing.
  note: by Matthew A. Carlton, Jay L. Devore.
  subject:
    topic: Statistics
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistics, general
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Texts in Statistics
  identifier: 9781493903955
  identifier: http://dx.doi.org/10.1007/978-1-4939-0395-5
  record info:
    record creation date: 140902
    record change date: 20151204185021.0
    record identifier: 978-1-4939-0395-5