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Essay / Research Paper Abstract
A 3 page paper presenting rationale for using nonparametric testing to measure the effects of use of a software package by salespeople in diverse sales regions. Senior management at Company W seeks appropriate evaluation measures to determine the potential usefulness of the software to the sales force. The purpose here is to provide “possible null and alternative hypotheses for a non-parametric test on this data using the chi-square distribution.” Bibliography lists 4 sources.
Page Count:
3 pages (~225 words per page)
File: CC6_KSstatsSoftAsse.rtf
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Unformatted sample text from the term paper:
Half of the salesforce of Company W has been testing a sales software over the past quarter. There are 250 salespeople evaluating the software, divided evenly among the
companys four sales regions. Each of the salespeople is expected to sell the same amount of product; there is no variation in points such as the size of sales
district; population contained within districts; geographical dispersion of sales outlets within the district; or other specific information that would disallow direct comparison of results obtained in one district with results
obtained in any - or all - other districts. Senior management at Company W seeks appropriate evaluation measures to determine the potential usefulness
of the software to the sales force. The purpose here is to provide "possible null and alternative hypotheses for a non-parametric test on this data using the chi-square distribution."
The Chi-Square Distribution The Chi-square distribution is defined by: f(x) = {1/[2/2 * (/2)]} * [x(/2)-1 * e-x/2] = 1, 2, ..., 0 < x (Electronic Statistics
Textbook, 2005) In the above equation, = degrees of freedom e = the base
of the natural logarithm, (Eulers e [2.71...]) G = (gamma) is the Gamma function (Electronic Statistics Textbook, 2005). At X2 = 0.4 and
degrees of freedom = 1, the Chi-square distribution takes on this appearance: At X2 = 0.493 and degrees of freedom = 50,
the Chi-square distribution becomes a bell curve, as can be seen at http://www.statsoft.com/textbook/glosfra.html. Though there are alternative uses of and approaches to
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