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Introduction to anova | PSY-7104 v6: Statistics I | Northcentral University

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Introduction to anova | PSY-7104 v6: Statistics I | Northcentral University The Analysis of Variance (ANOVA) method is the most popular and highly used statistical technique by researchers. Like T tests, ANOVAs are used to compare the means of groups for a given independent variable to determine whether they are statistically different from each other. However, T tests can only compare two groups. ANOVAs allow you to compare two or more (usually, ANOVAs are conducted with at least three groups). Using ANOVA, you can compare all mean differences simultaneously. This is advantageous as using multiple t tests increases the rate of Type I error, which means rejecting the null hypothesis when it is true (Tarlow, 2016). For example, say you are interested in whether socioeconomic status is related to individuals’ self-reported happiness. By separating the individuals into groups representing low, middle, and high socioeconomic status (or even low, low-mid, mid, mid-high and high, or some other combination of groups), you could then determine whether mean reported happiness is different across each of the groups. How many groups might you need to investigate in your own research? If the answer is more than two, then this will be an important week. This week, you will extend your knowledge by identifying and applying the use of a one-way ANOVA test. References/ Materials Tarlow, K. R. (2016). Teaching principles of inference with ANOVA. Teaching Statistics, 38(1), 16–21. Statistical reasoning for everyday life Bennett, J. O., Briggs, W. L.,

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