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The errors are random and independent of each other.
2. Each population has a normal distribution,
3. All population have the same variable.
I also learned that if I can not assume if the population has a normal distribution it is recommended to use the nonparametric Kruskal-Wallis test to compare data for more than two populations. The Kruskal-Wallis test is also used to analyze data that does not have a normal distribution. Interpretation of the Kruskal-Wallis test is basically similar to that of the parametric one way ANOVA however; nonparametric tests are usually simpler to calculate.
In the simulation, I made suggestions to review project plans and effort estimation, review testing procedures and increase channels for effective communication, although I should have done a two-way Anova instead...
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