simulation - 1 In this simulation, we study upon the...

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In this simulation, we study upon the statistics tool of ANOVA and Kruskal- Wallis tests. Both are used for analysis of data, but used for different reasons. The first lesson learned was that ANOVA tests assumes the population has a normal distribution and that the populations all have the same variance. Since these parameters are unreasonable to assume every population has, a Kruskal-Wallis test is used for when a population has a non-normal distribution, the errors are not random, or populations have different variances. Therefore major assumptions of ANOVA are: -Errors are random and independent -Each population has a normal distribution -All the populations have the same variance. The major assumptions of Kruskal-Wallis are: -The data does not have a normal distribution, or you cannot assume it is normal -The data is ordinal and not quantitative. Second lesson learned is if you are not sure which test to use it is recommended that you use the Chi-Square Goodness of Fit Test to check normality before deciding
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This note was uploaded on 12/21/2011 for the course ECON 101 taught by Professor Higgins during the Spring '11 term at University of Nevada, Las Vegas.

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simulation - 1 In this simulation, we study upon the...

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