ANOVA or analysis of variance allows one to use statistics to test the differences between two or more means and decreases the probability for a type 1 error, which might occur when looking at multiple two-sample t tests. Therefore, ANOVA is indicated for testing hypotheses where there are multiple means or populations. For instance we use the T-test in statistical analysis to know the difference between two means in a survey or experiment, such as the intervention group against the control group, were as on analysis of variance the data is calculated when there are three or more means of the populations need to be survey.

In most situation when two samples are investigated for the means outcome, the result will be the same for either the T-test or the ANOVA test. In a nutshell if you have more than two sample examine, the prefer test that will give accurate result is the ANOVA test, in the other hand more than two sample the result will increased on error. Therefore the ANOVA or analysis of variance give us the opportunity in statistics to calculate the differences between two or more means, and also decrease the probability of an error which might occur when looking at multiple two-sample T – test. Therefore, ANOVA is indicated for testing hypotheses where there are multiple means or populations (Making Connections:The Two-Sample t-Test,Regression, and ANOVA).

Reference:

Making Connections:The Two-Sample t-Test,Regression, and ANOVA. (n.d.). Retrieved March 18, 2015, from Pearson Highered: http://www.pearsonhighered.com/kuiper1einfo/assets/pdf/Kuiper_Ch02.pdf