In this tutorial I will teach you about ANOVA in excel 203. ANOVA stands for Analysis of Variance used in statistics. With this you are testing and checking different groups in order to check if there is a significant difference between them. For example if a company wants to change the packaging of the product, company could use the ANOVA to test the before and after of the product about the changes.

Before you perform ANOVA, you need a null hypothesis because using ANOVA means you are not only checking the variance between the groups, but also enable you to decide if you support or reject the null hypothesis.

If you don’t know the terms mentioned above, Please see the Statistics tutorial.

There are three types of ANOVA functions:

**Single factor ANOVA.**

ANOVA with single factor involves one group performing one task.

**Two factor with Replication.**

Two factor ANOVA with replication is done when there are 2 groups and the individuals within those groups are performing more than one activity.

**Two factor without Replication.**

Two factor ANOVA without replication can compare a single group of people who are performing more than one task.

We will do ANOVA in excel with an example of A doctor testing on weight loss techniques of patients. He takes 30 people. 10 goes into diet program. 10 under goes diet and exercise and another 10 in exercise program.

Click the Data Menu and click on the Data analysis tab. If you cant find the Data Analysis option, Go to the file menu and select options.

Select ANOVA single factor and click ok.

Click the input range box and select the data range and click the output range and select any blank cell and click ok.

This will automatically generate ANOVA tables that will have P-values, F-Values.

Generally, if the p-value is smaller than your Alpha level, you should reject the null hypothesis. If your F-value is larger than f-critical value, that would lead you to reject the null hypothesis.

Statistically, we can conclude that if F>F-crit, we will reject null hypothesis. In this case we will reject the null hypothesis. In order to check details about it, we will have to t-Test to test each.

Note that in two factor ANOVA, you can use more than two variables meaning that you don’t have to limit yourself to use only two variables.