Question: 1- Many statisticians base ANOVA on the design of the experiment, especially on the protocol that specifies the random assignments of treatment to subjects; the protocol's description of the assignment mechanism should include a specification of the structure of the treatments and of any blocking. It is also common to apply ANOVA to observational data using an appropriate statistical model.

Some popular designs use following types of ANOVA:

• One-way ANOVA is used to test for differences among two or more independent groups. e.g., different levels of urea application in a crop or different levels of effect of some medicine on groups of patients. However, the one-way ANOVA is used to test for differences among at least three groups, since the two-group case can be covered by t-test when there are only two means to compare.

• Factorial ANOVA is used when the experimenter wants to study the interaction effects among treatments.

2- When dealing with an uninformed person, it is good to make sure the explanations and the follow-up given is as simple as possible and accurate. Variance testing should first be explained as a way to get results from conducting a study or an experiment. There are one-way, two-way, three-way tests where the difference as indicated by their number is according to the variances analyzed in each of the study. One way will have one variable, while three way will have three variables. It is also necessary to make sure there is a connection between the different variables, as they need to come from the same population, and samples selected randomly

3- The analysis or ANOVA is a test that is conducted to find out if the survcey or experiments results are significant. There are different ways that this test might be done, depending on the study at hand. Statisticshowto described them as follows:

• One-way ANOVA between groups: used when you want to test two groups to see if there's a difference between them.

• Two way ANOVA without replication: used when you have one group and you're double-testing that same group. For example, you're testing one set of individuals before and after they take a medication to see if it works or not.

• Two way ANOVA with replication: Two groups, and the members of those groups are doing more than one thing. For example, two groups of patients from different hospitals trying two different therapies.

In order for the results to be accurate, ANOVA has the following assumptions in regards to the study:

• there needs to be similar variances

• the population where the samples are obtained should have normal distribution

• samples should be randomly selected

• samples should be independent