Multifactor Experiments

Helge Toutenburg
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Helge Toutenburg: University of Munich, Institute of Statistics

Chapter 6 in Experimental Design and Model Choice, 1995, pp 167-216 from Springer

Abstract: Abstract 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.

Keywords: Block Effect; Randomize Block Design; Total Response; Independence Model; Variance Table (search for similar items in EconPapers)
Date: 1995
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DOI: 10.1007/978-3-642-52498-1_6

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