This problem will introduce the learner to 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. Use the instructions for conducting an ANOVA on page 366 of the Bennett et al. (2014), or use an online calculator like: http://astatsa.com/OneWay_Anova_with_TukeyHSD/ 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