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Essay / Research Paper Abstract
This three page paper responds to the following questions: In ANOVA, what does F=1 mean? What are the differences between a two sample t-test and ANOVA hypothesis testing? When would you use ANOVA at your place of employment, in your education, or in politics? Why do we use nonparametric tests? Describe a psychological research situation or scenario that would use a nonparametric test. Why would the nonparametric test be used? Bibliography lists 3 sources
Page Count:
3 pages (~225 words per page)
File: MH11_MHanovttest.doc
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Unformatted sample text from the term paper:
actual variations of a group of averages collected from a subject population and the expected variation in group averages. When this F ratio is equal to 1, the variation
in group averages identified through the data collection process is the same as the expected variation of group averages, meaning that the null hypothesis that introduces the expected variation is
correct (ANOVA, 2008). While an ANOVA collects all the data into one ratio, the F ratio, and only finds on P value (significance) in relation to the null hypothesis,
a t-test gives the variations that occur when there are two specific groups, including an assessment of significance (p-value) in relation to the comparison between the two groups noted (Price,
2000). A t-test tool is created to understand comparisons between two separate populations, even if there are variations in the two populations. When testing a hypothesis utilizing a t-test
approach, a control and subject population are often utilized. When comparing outcomes of the testing process, a variable of 0.05 determines
whether the hypothesis is validated or whether the sets of numbers between the two populations determine too large a variation to support the hypothesis. If a p-value of 0.05
or less exists, then the hypothesis is validated and the numbers are considered the same; if a p-value of 0.05 or more exists, then the hypothesis is negated. The
decision to utilize a t-test rather than an ANOVA occurs in the presence of two groups, when the expectation is that the outcomes of the assessment will not show widely
different outcomes. An ANOVA is frequently used when comparative data is collected about individuals within one subject group, analyzing the impacts of
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