Analysis of Variance (ANOVA)

Analysis of Variance is a collection of statistical approaches or models. Each of these models is associated with a testing procedure. Using these procedures, we can effectively test the statistical significance between the two or more group means. Here idea is very simple- judge the apparent difference of different group means and these observations relate to the variance of the individual groups. ANOVA is capable of finding whether our samples are drawn from populations having same means. Thus ANOVA acts as a computational procedure used in cases like ‘multiple population’ and ‘multiple treatment on one population’. For testing the differences among three or more independent groups, one-way ANOVA is used. For the study of the effect of two or more treatment variables, factorial ANOVA is used. To check the dependent variable changes with the change in treatment, fixed effect model ANOVA is used. To deal with random variables, random effect model ANOVA is used. The ANOVA test is based on partitioning the variance of the observed responses into two groups, one group due to the level of each factor, and second group due to the in herent variability of the processes being simulated.