Limitations and Requirements of ANOVA Essay Example | Topics and Well Written Essays - 500 words

Limitations and Requirements of ANOVA - Essay ExampleThe sample distributions variances should not be different though close to departures can be accommodated. All individuals used in the samples must(prenominal) be selected randomly from the population. All individuals of the samples must have equal probability for being selected. The sizes of the sample should be equal but there is an accommodation of some differences. One of the limitations of ANOVA is that, when a significant data difference cannot be found, the samples cannot be tell to be the same. It only indicates differences between groups and not groups which atomic number 18 different.Normality assumes that the errors which ar random within from each one group of treatment, the groups mean deviations, have a normal probability distribution. For normal data but variances which are heterogeneous, ANOVA is respectable for balanced designs but not for designs which are highly unbalanced. In normal data setting, hete rogeneous variances and designs which are unbalanced, Welchs ANOVA king be used for the accommodation of unequal variances. With variances which are homogenous but data which is non-normal, ANOVA is good for designs which are balanced with large samples. It is not good for unbalanced designs with sm altogether samples. In non-normal data setting, variances which are homogenous and a small sample or unbalanced design, a non-parametric procedure is preferred. If the distribution of data is not normal and heterogeneity of variances exist, there might be transformation necessity. The importance of a design which is balanced and existence of a large sample must be put into consideration. A common standard deviation is shared by all normal distributions.The different t-test options can be used around the equal variances assumptions or unequal variances assumption. The f-test, away from being used to for t-tests, it can also be used to compare variations in two data sets in the CJ data. The test makes use of a calculated F stat