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Essay / Research Paper Abstract
This is a 3 page paper that explores statistical topics. Alpha values and the dangers in inferential statistics are explored. Bibliography lists 2 sources.
Page Count:
3 pages (~225 words per page)
File: KW60_KFlstat4.doc
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tests may occur, undermining the value of the tests at all. In order to ensure that statistical tests produce results that are legitimately in accordance with reality, assurance must be
used. For example, one might look at the research put out by the National Institute of Mental Health, which attests to there being some 3 million sociopathic Americans. In data
produced by Darden, however, he produces a count of some 15 million such individuals. This is quite a significance variant in data, so how it is that such an error
was produced? The reason for these results is likely due to the fact that inferential statistics are naturally prone to two sources of error (Sommer, 2010). Should either of
these occur, the statistical results will not truthfully represent the actual nature of reality. The first possible error is a sampling error. This can occur when a sample is selected
that does not adequately represent the true make-up of the population as a whole (Sommer, 2010). The chances of this error can be reduced through using multiple test groups where
possible. The other type of error is the sampling bias, wherein the strategy used to gather the sample is in itself flawed, such that no matter how many tests are
performed, the same inaccuracies will be repeated (Sommer, 2010). This can be offset by always using an appropriate sample selection method, usually randomized and stratified selection. When looking at
the discrepancies produced in Dardens work, it is clear that an error has taken place. Exactly what caused it is difficult to determine without further information. It may well be
that Dardens results contained some "random chance" element wherein his sample, by matter of chance, contained more sociopathic people than the true average. It may also be that Dardens sampling
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