This problem will introduce the learner into a technique called Analysis of Variance. For this course we will only conduct a simple One-Way ANOVA and touch briefly on the important elements of this technique. The One-Way ANOVA is an extension of the independent –t test that can only look at two independent sample means. We can use the One-Way ANOVA to look at three or more independent sample means. Use the following data to conduct a One-Way ANOVA: Scores Group 1 1 2 1 3 1 2 2 3 2 4 2 4 3 5 3 6 3 Notice the group (grouping) variable, which is the independent variable or factor is made up of three different groups. The scores are the dependent variable. a) What is the F-score; Are the results significant, and if so, at what level (P-value)? b) If the results are significant to the following: Click analyze, then click Compare Means, and then select one-way ANOVA like you did previously. Now click Post Hoc. In this area check Tukey. If there is a significant result, we really do not know where it is. Is it between group 1 and 2, 1 and 3, or 2 and 3? Post hoc tests let us isolate where the level of significance was. So if the results come back significant, conduct the post hoc test as I mentioned above and explain where the results were significant. c) What do the results obtained from the test mean?
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