Applying ANOVA and Nonparametric Tests Simulation
This simulation made me make business decisions based on different kinds of tests. And making decisions based on the results. At first the simulation provided background information about the company and then it created the issue and I had to make decisions. I was given a choice to pick between a One-way ANOVA or Kruskal-Wallis and I chose the Kruskal-Wallis test. I chose that test because it is better to use it when the test is tricky to congregate all of the assumptions of an ANOVA test. The Kruskal-Wallis test is considered to be a nonparametric alternative to a one way ANOVA. When comparing three or more samples, this test is used over the ANOVA; it is to test the null hypothesis that the different samples in the comparison drawn from the same distribution or from distributions with the same median. Nonparametric tests for the main part are simpler to calculate than the Kruskal-Wallis test. The way to approach the Kruskal-Wallis test is similar to the parametric one way ANOVA. The crop issue on the simulation can be tested the same way everyday situations, such as sport stats and weather stats.
In the simulation I had to apply the concepts and use the analytical tools. Suggestions were made to review the project plans and effort estimation, to increase channels for effective communication and review testing procedures. I was graded on my suggestions and it told me that I should of set up a two way ANOVA with a schedule variance as factor A and number of defects as factor B and coming to the conclusion of a difference in the means due to a schedule variance, number of defects, and the interaction of schedule variance and number defects. If the research issue was more complex a ANOVA test would have been the better choice, because it is more flexible and at the same time a more powerful technique. This simulation gave me a better understanding of what ANOVA and how it allows us to notice interaction effects...
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