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Applying ANOVA and Nonparametric Tests SimulationUniversity of PhoenixResearch and Evaluation IIRES 342ContentsSubjectPageIntroduction………………………………………………………………………3Lessons Learned……….………...………………………………………………… 3Recommendations…………………………………………………………………..4Conclusion ……………………………………………………………………….... 5References…………………………………………………………………………. 6IntroductionUsing analysis of variance (ANOVA) and Nonparametric Tests Simulation required for this week's exercises had one take part in a four-month analysis of Praxidike Systems. Praxidike is a software firm that provides and develops a wide variety of software solutions to a diverse cliental list. The simulation involved analyzing variables like productivity and customer satisfaction. The simulation requires one to decide on which method of testing would be used and then present suggestions based on the results.A company that uses AVOVA in the quality management process will help a company and steer those in the decision-making role to identify opportunities and challenges. ANOVA can be used to guide the company to necessary changes that will improve the problem areas uncovered. Applying nonparametric tests, such as the Kruskal-Wallis test, and ANOVA allows a business to determine the causes of the poor quality. ANOVA assumes that each population being studied has a normal distribution, that errors are random and independent of each other, and that all the populations have the same variance. It is not always possible to make these assumptions and a nonparametric test, such as the Kruskal-Wallis can be used for analysis (Apollo Group 2009). In this paper there will be a summary of the simulation, what lessons were learned relative to the ANOVA and Nonparametric tests, and how they can be applied in the workplace.Lessons LearnedBeing the Quality Assurance Manager for Praxidike Systems, one must make sure the clients are satisfied and delivery is on time. One lesson learned is in order to make a decision...

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