Reference no: EM13243942
1.) The discussion surrounding the ANOVA is very important. This is a widely utilized statistical tool. What is the ANOVA? What is the purpose of the ANOVA? What role does variation have in the discussion? What is the purpose of the F distribution?
2.) Why is the F distribution important? How do you determine if a significant difference exists among the groups in ANOVA? How do you determine differences between the groups in ANOVA?
3.) Describe the requirements that must be met before an ANOVA test can be used. Discuss what the researcher should do if one of these requirements is not met.
4.) How could the Analysis of Variance be used to make decisions in a dynamic, competitive business environment? In what situations does your organization use ANOVA? What are some examples that you are familiar with or where ANOVA could be used?
5.) What is the role or significance of the Tukey Honestly Significant Difference test?
6.) What are the purposes of nonparametric methods? How do these compare to parametric tests?
7.)Define what the chi square distribution is. Why do you use the chi-square statistic? What type of data is used with chi square analysis? What are some limitations of the distribution? What is the goodness of fit test?
8.)Can the formal hypothesis testing approach be used for nonparametric tests? How are parametric and nonparametric statistics different? How are parametric and nonparametric statistics similar?
9.) What are some other non-parametric tests (3)? What role or purpose does each serve? What would be a comparative parametric test for each non-parametric test?
10.) Another set of nonparametric methods deals with the analysis of ranked data. When and why would you utilize these various methods? How do these tests relate to the one that have been discussed previously in this class? Compare and contrast.
11.) Under what circumstances a nonparametric test should be utilized? Explain.
What are the strengths and weaknesses of nonparametric tests? Can the outcomes of nonparametric tests be generalized to populations?
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