Examples of designed experiments with nonnormal responses

Sharon L. Lewis, Douglas Montgomery, Raymond H. Myers

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

Many industrial experiments involve nonnormal response variables. Generalized linear models (GLM) are a useful alternative to the traditional methods for analyzing such data based on transformations. In this paper we present several examples of designed experiments with nonnormal responses. For each example, models are built using classical least squares methods applied to the appropriately transformed data and models are also built using the GLM. The models are compared by examining the length of the confidence interval about the mean response stated in original units. We show that GLM is an excellent alternative to the transformation approach.

Original languageEnglish (US)
Pages (from-to)265-278
Number of pages14
JournalJournal of Quality Technology
Volume33
Issue number3
StatePublished - Jul 1 2001

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Keywords

  • Design of experiments
  • Generalized linear models
  • Nonconstant variance
  • Nonnormal response

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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