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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