Academic Integrity: tutoring, explanations, and feedback — we don’t complete graded work or submit on a student’s behalf.

berore class (11 AM) on Nov 16. 1). See problem 13 on p. 424-5 (Chapter 15). Thi

ID: 3362428 • Letter: B

Question

berore class (11 AM) on Nov 16. 1). See problem 13 on p. 424-5 (Chapter 15). This was also discussed in class on 24 & 2 6 hr reserve in the Library. Exam choices below, choose the answer with the two biggest potential problems you would face using ANOVA to test for differences in the means of these three groups. Oct. If you forgot, read the problem in the textbook. The textbook is also on 1 nine the histograms of data below. From the In other words, what violations of the assumptions should you be concerned about ? (see p. 403). Do not assume there are problems w unless they are explicitly mentioned! Read each statement completely-the correct answer has both problems, not just one ! As in homework #4, you should be able to LOOK at these distributions and make decisions a. The measurements of Resistance are ranks and they are not normally distributed b. The measurements of Resistance are not normally distributed in all three groups and the variances differ between the low group and the other two groups c. The measurements of Resistance are not normally distributed in the high and medium groups and the variances are the same in all the groups d. The shapes of the distributions differ dramatically between the medium and high groups and the measurements from different years are not independent. 11-1 0.5 0.6 0.7 08 0.9 Resistance Chanter 17- Regression

Explanation / Answer

By looking at the three histograms of measurements of resistance we can figure out that the three measurements are not normally distributed and also data of low group is more spread out than the measurements of the high group. In other words, the variance of the low group is greater than the variance of the high group.

These are the main two problems we would face in ANOVA testing as the main assumptions in ANOVA are that Data should be normally distributed and variance of the data should be normal.

ANOVA is generally robust for assumptions but too much deviation of variance and violation of Normally distribution assumption will get the user into trouble.