Abstract: This chapter discusses the general strategy of significance testing. In literary contexts, significance testing can be useful in connection with authorship attribution. The first step in significance testing is to formulate a hypothesis. The hypothesis in a significance test is about the value of a population parameter. A specific hypothesis about the relation between two parameters is called the null hypothesis, and it plays a special part in significance testing. If one is testing two texts in the course of trying to decide whether they are by the same author, there are various differences between word frequencies, word and sentence length, and the like. One sets up the null hypothesis that there is no difference between these parameters in the populations from which the passages are drawn and that the variations that are observed are because of sampling error. If the chance probability of the observed divergences is less than the level of probability fixed in advance, the null hypothesis is rejected.
Publication Year: 1982
Publication Date: 1982-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 4
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