The ANOVA, also known as analysis of variance, is a statistical method used to test if the results of a survey are significant or not. In other terms, the test is meant to determine whether a researcher should reject the null hypothesis or accept the alternate hypothesis (Mackenzie, 2018). The test is used to determine whether there is a difference between groups. For example, an ANOVA test can be used to determine which therapy for psychiatric patients between counseling or medication is more effective.
There are two types of ANOVA, ‘one-way’ ANOVA and ‘two-way ANOVA. One-way ANOVA has one independent variable with two layers. It is used to gain more information on the impact of the dependent variable on the independent variable. It can be used to determine the relationship between one or many dependent variables on the independent variable. Its null hypothesis (H0) is that there is no difference between the groups and equality between the means (Mackenzie, 2018). On the other hand, its alternate hypothesis (H1) is that there is a difference between the means of the groups. For example, it is used to determine the effectiveness of various types of medicines in treating malaria.
On the other hand, a two-way ANOVA is used to determine the impacts of more than one independent variable on a dependent (Mackenzie, 2018). For example, it is used in a statistical test examining the implications of age and gender and age on infant weight. While age and gender are independent variables, infant weight is a dependent variable.
Interaction effects arise when one variable depends on the value of another variable. An interaction effect occurs when the impact of one factor directly depends on the level of the other factor (Frost, J2021). For example, drug intoxication depends on the amount of alcohol or drug substances an individual consumes, such that the more alcohol consumption, the higher the intoxication levels.
References
Frost, J. (2021, June 10). Understanding interaction effects in statistics. Statistics ByJim. https://statisticsbyjim.com/regression/interaction-effects/
Mackenzie, R. J. (2018, July 20). One-way vs. two-way ANOVA: Differences, assumptions, and hypotheses. Informatics from Technology Networks. https://www.technologynetworks.com/informatics/articles/one-way-vs-two-way-anova-definition-differences-assumptions-and-hypotheses-306553
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