Model and Data Checking

  • Glen McPherson
Chapter
Part of the Springer Texts in Statistics book series (STS)

Abstract

Even the most careful and thorough experimental practice cannot eliminate the possibility of an error appearing in the data collected from an experiment. It may arise because of a simple mistake in recording or transcribing a result, be due to a fault in a recording device, or perhaps result from an undetected fault in an experimental unit or an unknown affliction suffered by a subject used in the experiment. In many circumstances, it is possible to detect serious errors in the data. In other circumstances, it can be determined in advance that the nature of the experimental design will make detection either impossible or difficult.

Keywords

Model Check Trend Line Distributional Assumption Normality Assumption Probability Plot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Glen McPherson
    • 1
  1. 1.School of Mathematics and PhysicsThe University of TasmaniaHobartAustralia

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