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Analysis of variance is a statistical procedure that compares data between two or more groups or conditions to investigate the presence of difference between those groups on some continuous dependent variable (Grove, Cipher, 2017). ANOVA is the recommended statistical technique for checking the difference between more than two groups. The formulas for ANOVA compute two estimates of variance: one estimate represents differences between two groups or two conditions. The other estimate represents differences among or with in the data.

For example; Cancer patients involving three experimental groups, One with chemo and radiation treatment, one with chemotherapy treatment, one with radiation treatment and compare the effect of treatment.

Use of the ANOVA involves the following assumptions:

 1. Sample means from the population are normally distributed.

2. The groups are mutually exclusive.

3. The dependent variable is measured at the interval/ratio level.

4. The groups should have equal variance, termed “homogeneity of variance.”

5. All observations within each sample are independent.

Grove, S., & Cipher, D. (2017). Calculating  ANOVA and post Hoc Analysis flowing ANOVA [Digital image]. PP377, Retrieved April 3, 2017, from https://viewer.gcu.edu/aVQYDA