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Essay / Research Paper Abstract
This is a 3 page paper that provides an overview of statistical tests. Tests such as ANOVA and t-tests are explored. Bibliography lists 3 sources.
Page Count:
3 pages (~225 words per page)
File: KW60_KFsta010.doc
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Unformatted sample text from the term paper:
eight paid volunteers were placed (individually) in a room in which there was no light from the outside and no clocks or other indications of time. They could turn the
lights on and off as they wished. After a month in the room, each individual tended to develop a steady cycle. Their cycles at the end of the study were
as follows: 25, 27, 25, 23, 24, 25, 26, and 25. Using the .05 level of significance, what should we conclude about the theory that 24 hours is the natural
cycle? (That is, does the average cycle length under these conditions differ significantly from 24 hours?) (a) Use the steps of hypothesis testing. Hypothesis testing is
often used in statistics for the purpose of determining whether or not there is a significant difference (i.e. - a different not due to mere chance) between a sample mean
and a population mean. This can be utilized to make a variety of statistically important inferences, such as in the above example, which asks one to compare the experiences of
the sample of the eight people who participated in the study with the supposed mean of the general population, which is 24 hours. Hypothesis testing will be highly useful for
performing this comparison. The first step of statistical hypothesis testing is to establish the two hypotheses to be tested; generally, these are referred to as the null hypothesis (h0)
and the alternative hypothesis (h1) (Gerstman, 2006). The null hypothesis is always synthesized to express "no difference" between the two means under examination, while the alternative hypothesis is always synthesized
to express "a difference in" the two means under examination (Gerstman, 2006). This means the null hypothesis, h0, could be expressed as "the sample mean will be equal
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