Hypothesis Identification Article Analysis
Hypothesis Identification Article Analysis In this paper I will show how ANOVA for business data research was used to compare the means for business data from different populations.
ANOVA’s for business Data research was comparing means for business data from different populations. The article shows how sample data is taken from different and independently from different sources and different variances may exist this hypothesis test may show that there is a violation of the equal variance assumption as a result the traditionally one way method may not be statically justifiable. This test used several different ways to show how the old variance was still possible and to then show how the one way method was no longer relevant it will also show how the new variance should be more acceptable than the old variance.
The hypothesis took the F test and studied it in four different ways. The first was finite-sample distribution under hypothesis. The second test was the empirical type 1 error rate versus the significance level. The third test was power performance and the last test was empirical comparison with the one way ANOVA F-test. These different test show how each was relevant to each other it also compared all of the data collected from the test to see which test came close to proving the one way method was not relevant or to show which test to show that the one way test was still relevant.
In this hypothesis paper I took information from a ANOVA to show if the one way method was still a relevant method of testing or if there was a different method that would make the one way method relevant. I also showed the four different test that was used to help prove wither the one way method was relevant or not relevant any