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: Designing Quantitative Experiments
    sub title: Prediction Analysis
  name:
    name part: Wolberg, John.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 208 p. 49 illus. online resource.
  abstract: The method of Prediction Analysis is applicable for anyone interested in designing a quantitative experiment. The design phase of an experiment can be broken down into problem dependent design questions (like the type of equipment to use and the experimental setup) and generic questions (like the number of data points required, range of values for the independent variables and measurement accuracy). This book is directed towards the generic design phase of the process. The methodology for this phase of the design process is problem independent and can be applied to experiments performed in most branches of science and technology. The purpose of the prediction analysis is to predict the accuracy of the results that one can expect from a proposed experiment. Prediction analyses can be performed using the REGRESS program which was developed by the author and can be obtained free-of-charge through the author's website. Many examples of prediction analyses are included in the book ranging from very simple experiments based upon a linear relationship between the dependent and independent variables to experiments in which the mathematical models are highly non-linear.
  table of contents: Statistical Background -- The Method of Least Squares -- Prediction Analysis -- Separation Experiments -- Initial Value Experiments -- Random Distributions.
  note: by John Wolberg.
  subject:
    topic: Physics
  subject:
    topic: Physical measurements
  subject:
    topic: Measurement
  subject:
    topic: Statistics
  subject:
    topic: Engineering
  subject:
    topic: Physics
  subject:
    topic: Measurement Science and Instrumentation
  subject:
    topic: Engineering, general
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  classification: T50
  classification: 530.8
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783642115899
  identifier: http://dx.doi.org/10.1007/978-3-642-11589-9
  record info:
    record creation date: 100623
    record change date: 20151204153020.0
    record identifier: 978-3-642-11589-9