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Essay / Research Paper Abstract
This is a 3 page paper that provides an overview of parametric testing. The value of ANOVA in non-normal distributions is explored. Bibliography lists 2 sources.
Page Count:
3 pages (~225 words per page)
File: KW60_KFanovax.doc
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Unformatted sample text from the term paper:
of influence. This is useful in hypothesis testing, and is the backbone of much research. However, there are occasions when such tests are not sufficient for the research task at
hand. For example, the statistician might encounter a situation which requires the capacity to determine the equality of means across several groups. This is problematic to solve through basic t-tests,
especially in contexts where multiple source of variation are at work upon the variables. To use the t-tests in such a situation would result in an increased frequency of type
I errors. In such cases, an analysis of variance (ANOVA) is the preferable method. This paragraph helps the student present an overview of analysis of variance. Through the process of
ANOVA, one can analyze the equality of means across multiple groups, with multiple impacting factors, without needing to resort to the testing of a large number of groups that would
be necessitated through t-testing ("ANOVA", 2011). If one tested a massive number of groups through t-testing, the number of required pairings to test for the significance of multiple factors would
require an exponentially increasing number of pairs ("ANOVA", 2011). As pairs increase, one encounters outlying anomalies with great frequency; one "should not be surprised to observe things that happen only
5% of the time" ("ANOVA", 2011). In other words, a variance with P of .05 could not realistically be considered statistically significant ("ANOVA", 2011). With ANOVA, one P value is
produced for all groups. Therefore, one could test for the variance of multiple factors related to the value of majors if one were attending college. For instance, if one were
concerned about the profitability of a major, or the likelihood of finding work relevant to ones major, one could use ANOVA to analyze multiple majors to determine which are most
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