Comparison of Two Samples

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

Chapter 2 in Experimental Design and Model Choice, 1995, pp 23-44 from Springer

Abstract: Abstract Problems of comparing two samples arise frequently in medicine, sociology, agriculture, engineering, or marketing. The data may have been generated by observation or may be the outcomes of a controlled experiment. In the latter case, randomization plays a crucial role in gaining information about possible differences in the samples which may be due to a specific factor. Randomization means, for example, that in a controlled clinical trial there is a constant chance for every patient of getting a specific treatment. The idea of a blind, double blind, or even triple blind setup of the experiment is that neither patient, nor clinician, nor statistician know what treatment has been given. This should exclude possible biases in the response variable, that would be induced by such knowledge. It becomes clear that careful planning is indispensible to achieve valid results.

Keywords: Independent Group; Standard Normal Distribution; Binary Response; Exact Distribution; False Decision (search for similar items in EconPapers)
Date: 1995
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DOI: 10.1007/978-3-642-52498-1_2

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