Analyzing data from designed experiments: A regression tree approach

James W. Wisnowski, George Runger, Douglas Montgomery

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Regression trees are an algorithmic procedure used to partition the space of a set of independent or predictor variables with the objective of finding the combination(s) of predictor variable levels that produce a desired value for some response. They have been used in several fields, notably medical diagnosis and the analysis of large data sets. We have observed that regression trees are a useful supplement to the standard analysis tools for designed experiments. Illustrations of regression trees applied to 2k factorial designs are provided. We show that the use of a regression tree can often provide insights to the analyst more easily and more directly than can the standard factorial design analysis.

Original languageEnglish (US)
Pages (from-to)185-197
Number of pages13
JournalQuality Engineering
Issue number2
StatePublished - 1999


  • CART
  • Classification and regression trees
  • Factorial designs

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering


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