1431 Words6 Pages

Nonparametric Test
Education is even more important than ever today for anyone interested in entering the world of employment with either large international corporations, or even local vendors serving the community within the area where one lives. In an ongoing effort by our research team to determine if the difference in the wages from our sample population of men and women, who have various levels of education, does in fact make the difference. We are looking to use an additional test to discover whether or not we can inconclusively state that from our previous test conclusion that our team believes that there is a difference in the wages of the sample population.
In our investigation, the team will hope to convince the audience of*…show more content…*

After that, the team had to calculate the test statistic by using the Appendix B worksheet rank sum sample size and rank sum from each group. The following formula gives the results of that worksheet Our team then made our decision that because the test statistic of 18.51 is far greater then that of the Chi-square value at v = 4, = .05 in Appendix E, we must reject the null hypothesis that all c populations are the same (2007). These results can be viewed in Appendix D, where at the significance level of .05, it shows the Chi-square of 25.75, which is still far above the level for the team to reject the null hypothesis that all c population medians are the same. The team continues the research by giving details to the nonparametric test we used and why we opted to use it. Explain Kruskal-Wallis Test The use of the nonparametric test teaches all researchers to use smaller sample, normality is not a requirement, and can be used for ordinal (ranked) data. The reason for our team choosing the Kruskal-Wallis test is that; one, it is the corresponding test to the One Factor ANOVA test that we ran in the previous research paper of week three; two the team was able to compare independent samples from the five different groups even though the sample sizes were not the same, but did include the minimum of five

After that, the team had to calculate the test statistic by using the Appendix B worksheet rank sum sample size and rank sum from each group. The following formula gives the results of that worksheet Our team then made our decision that because the test statistic of 18.51 is far greater then that of the Chi-square value at v = 4, = .05 in Appendix E, we must reject the null hypothesis that all c populations are the same (2007). These results can be viewed in Appendix D, where at the significance level of .05, it shows the Chi-square of 25.75, which is still far above the level for the team to reject the null hypothesis that all c population medians are the same. The team continues the research by giving details to the nonparametric test we used and why we opted to use it. Explain Kruskal-Wallis Test The use of the nonparametric test teaches all researchers to use smaller sample, normality is not a requirement, and can be used for ordinal (ranked) data. The reason for our team choosing the Kruskal-Wallis test is that; one, it is the corresponding test to the One Factor ANOVA test that we ran in the previous research paper of week three; two the team was able to compare independent samples from the five different groups even though the sample sizes were not the same, but did include the minimum of five

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