# Analysis of Variance: Anova

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Analysis of variance (ANOVA): How and when it is used in research In statistics, variance refers to the comparison of the means of more than two groups. The term "variance may mislead some students to think the technique is used to compare group variances. In fact, analysis of variance uses variance to cast inference on group means...Whether an observed difference between groups mean is 'surprising' will depends on the spread (variance) of the observations within groups. Widely different averages can more likely arise by chance if individual observations within groups vary greatly" (Analysis of variance. 2012, Stat Primer). Variances indicate the presence of change or the existence of a statistically significant difference between two groups being compared. For every statistical experiment, an alternative hypothesis and a null hypothesis is constructed. If "the variance between groups exceeds what is expected in terms of the variance" the null has been disproven and the independent variable is shown to have had a measurable influence upon the experimental population (Analysis of variance. 2012, Stat Primer). In statistical experimentation, the hypothesis (which the experimenter actually thinks or hopes will occur) is never technically proven; rather the null hypothesis is refuted. The actual hypothesis of the experimenter is 'guilty until proven innocent' (What is a null hypothesis, 2012, Null Hypothesis). A good example of the use of a null hypothesis might be found