When is the Analysis of Variance or ANOVA test used?
Since this is not my area of expertise, I searched Google under the key words "anova test" to get these possible sources:
http://en.wikipedia.org/wiki/Analysis_of_variance
http://www.physics.csbsju.edu/stats/anova.html
http://www.experiment-resources.com/anova-test.html
In the future, you can find the information you desire more quickly, if you use appropriate key words to do your own search. Also see http://hanlib.sou.edu/searchtools/.
I hope this helps. Thanks for asking.
The Analysis of Variance (ANOVA) test is used when we want to compare the means of three or more groups to determine if there is a significant difference between them. It is a statistical technique that allows us to investigate the variation between groups, as well as the variation within groups.
To perform an ANOVA test, follow these steps:
1. Define the null hypothesis (H0) and alternative hypothesis (Ha): The null hypothesis states that there is no significant difference between the means of the groups, while the alternative hypothesis states that there is a significant difference between at least two group means.
2. Select an appropriate ANOVA test: There are several types of ANOVA tests, such as one-way ANOVA, two-way ANOVA, and repeated measures ANOVA. Choose the appropriate test based on the design of your study or experiment.
3. Collect and organize the data: Gather data from each group and organize it in a way that allows you to compare the means between groups.
4. Calculate the test statistic: Depending on the type of ANOVA test, you will need to calculate the appropriate test statistic. For example, in one-way ANOVA, the test statistic is the F-statistic.
5. Determine the critical value or p-value: Determine the critical value or p-value to compare with the test statistic. If the test statistic exceeds the critical value or if the p-value is less than the significance level (usually 0.05), then you can reject the null hypothesis and conclude that there is a significant difference between the means of the groups.
6. Interpret the results: Analyze the results and interpret the findings in the context of your study. If there is a significant difference, you may need to perform post-hoc tests to determine which specific groups differ from each other.
It is important to note that ANOVA assumes certain assumptions, such as normality and homogeneity of variances, which should be checked before conducting the test.