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APPLICATION OF INFERENTIAL STATISTICAL TESTS APPLICATION OF INFERENTIAL STATISTICAL TESTS

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Essay / Research Paper Abstract

This 5 page paper discusses the application of inferential tests on the real world. Using a fictional test which predicts the increase of productivity to a person's exercise in the morning before work. Description of variables, probability and a mention of chi-square. Bibliography lists 4 sources.

Page Count:

5 pages (~225 words per page)

File: D0_MBsiht.rtf

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Unformatted sample text from the term paper:

example of this would be when a person leaves school and attempts to understand the professional manuals or to do some research for their employer. Consequently, the specific words we use to communicate results of data analyses can have an impact on others (and our own) understanding of the meaning of statistical tests. Evidence indicates that many scientists fail to accurately interpret the meaning of common statistical analyses used to test hypotheses. A solution to this problem may very well be in the way inferential statistical tests are applied in the real world. A quick example might be to see if people who exercise in the morning are actually more efficient at their jobs during the day. If one were to merely examine the productivity of the employee in relationship to the workout in the morning, then this would be considered a correlational study and not an inferential one. However, if one were to measure those who workout in the morning as opposed to those who did not, and then compared their productivity in the workplace, this would then be an inferential test. Suppose it was found that eighty-six percent of the people who worked out were more productive, with a mean mark of seventy-nine percent for those who did not work out. This would reduce the inferences to only two possible choices: Exercising in the morning before work increases productivity, or the difference in productivity is purely coincidental. Now, given that these are the only two choices, one could consider using a null hypothesis, which would, point blank, state that exercise before work has no effect on productivity. The experiential hypothesis would state the other end of the spectrum, which is that exercise definitely increases the productivity of the employee. Unfortunately, neither of ...

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