Abstract
As specified in Chapter 5, there is an experimental design for dealing with variables whose effect on the response variable we are not interested in. Designs of this sort are known as block designs, and the variables whose effect is to be eliminated are known as blocking variables. This chapter discusses the process for analysing data collected from experiments designed thus. Firstly, we will address the case where there is one variable that is not of interest (section 9.2) and then go on to review the analysis process when there are several blocking variables (section 9.3, 9.4 and 9.5). A somewhat special analysis has to be conducted when any of the response variables that should have been gathered are missing. We look at how to do this analysis in section 9.6 Finally, in section, 9.7, we will examine the case where the block size is smaller than the number of factor alternatives, which we referred to as incomplete block designs in Chapter 5.
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Notes
Remember that as discussed at the beginning of this chapter, the effects are calculated by the difference between the mean of the observation for the variable in question (y;.., y;., y..~,respectively) and the grand mean (0.4)
The derivative of a function is equalled to 0 to find out the minimum or the maximun; in this case the minimun.
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© 2001 Springer Science+Business Media New York
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Juristo, N., Moreno, A.M. (2001). Experiments with Undesired Variations. In: Basics of Software Engineering Experimentation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3304-4_9
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DOI: https://doi.org/10.1007/978-1-4757-3304-4_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5011-6
Online ISBN: 978-1-4757-3304-4
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