Multifactor Experiments

  • Helge Toutenburg


In practice, for most designed experiments it can be assumed that the response Y is not only dependent on a single variable but on a whole group of prognostic factors. If these variables are continuous, their influence on the response is taken into account by so-called factor levels. These are ranges ( e.g., low, medium, high) that classify the continuous variables as ordinal variables. In Sections 1.7 and 1.8, we have already cited examples for designed experiments where the dependence of a response on two factors was to be examined.


Block Effect Randomize Block Design Total Response Independence Model Variance Table 
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-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Helge Toutenburg
    • 1
  1. 1.Institute of StatisticsUniversity of MunichMunichGermany

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