Analysis of variance (ANOVA) can be described as the statistical method used to test if
all the groups of a study are influenced by same variables and if so, whether
they are influenced to the same degree (Sagepub, 2016) . ANOVA is used to test
the general differences among means rather than specific differences. This
method is used when tests are done separately on each group. After completion
of the study, the results are compared and by using analysis of variance we can
find out if the average of independent groups are similar and the study the
impact of variables (Lane, 2007).
So we can say that
ANOVA calculates the mean for each of the final grading groups (HD, D, Cr, P, N) on the tutorial exercise figure – the Group Means.
It calculates the mean for all the groups combined – the overall Mean.
Then it calculates, within each group, the total deviation of each individual’s score from the Group Mean – Within Group Variation.
Next, it calculates the deviation of each Group Mean from the Overall Mean – Between Group Variation.
Finally, ANOVA produces the F statistic which is the ratio Between Group Variation to the Within Group Variation.
If the Between Group Variation is significantly greater than the Within Group Variation, then it is likely that there is a statistically significant difference between the groups.
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