MINDTAP From Cengage Week 11 Homework Due on Nov 20 at 3 AM BRST 12. Heasuring e

Question

MINDTAP From Cengage Week 11 Homework Due on Nov 20 at 3 AM BRST 12. Heasuring effect size for two-factor ANOVA It is projected that approximately 580,000 veterans will take advantage of the Gt for the 21st Century. Boots to Books is a course for all veterans, current military members, and their family members, frends, and supperters. The goel of Boots to Books is to assist deployed, postdeployed, and veteran students in making positive transition from mlitary to cidiarife or from deployment to postdeployment lfe, including the acquisition of college survival skills. Post-traumatic stress disorder (PTSD) is quite common among combut veterans. Suppose that a researcher wants to revise the Boots to Books course in order to reduce the effects of PTsD. He recruits a group of combat veterans and collects data on the kength of time they were in the military (Mactor A) and the potential components of the revised course ournaling, community service, physical activity, and medtation: factor 8). He then assigns them one of the four components. The study will evaluete which components of the program are the most efflective for reducing PTso symptoms. The results of the hypothetical study are summarized in the following data matrix. Each cel reports the average (M), the total (T), and the sum of squares (SS) of the symptom score (x) on the Clinician-Administered PTSD Scale (CAPS) of 10 veterans. Veterans are grouped according to the number of years they served in the military Factor B: Program Component Community Physical eurnaling Service Activity Meditation M-48.5M 48.5 M-53 M-54 M-49.5 -485 M- 485 Years in Mälitary SS 62.5 ss 112.5055 -52.5 S5-52.5 M-50.5 M-50.5 M 49.5M 49 S 152.5 SS 202.5 55- 62.5 55- 60 1,485 1,485 1,510 1,515 The researcher performs an analysis of variance (ANOVA) to test the hypothesis that the populations defined by the treatment combinations are equal The results are presented in the folowing ANOVA table. 362 2917 80.4167 25.6250 236 2500 Between treatments Factor A Factor B AXB interaction 40.2083 3.3 8.5417 0.7 42.7083 3.51 2.1528 108 Total 1,674.7917 use the significance level ·01 to complete the folowing condusions. The critical F value for factor A (years in miitary) is 4.81. Therefore, the main effect due to factor A is The critical F value for factor B (program component) is 3.97, Therefore, the main effect due to factor B is The cntical F value for the interaction of factors A and B is 2.97. Therefore, the effect cue to the interaction of factors A and B is

Explanation / Answer

From the given output the F test statistics value corresponding to factor A is 3.31

Decision rule :

1) If F test statistic value < F critical value then we fail to reject the null hypothesis.

2) If F test statistic value >= F critical value then we reject the null hypothesis.

For factor A , F test statistic = 3.31 < 4.81 = = critical value, so we fail to reject the null hypothesis.

Conclusion: The main effect due to factor A is not significant at 1% level of significance.

For factor B , F test statistic = 0.7 < 3.97 = critical value, so we fail to reject the null hypothesis.

Conclusion: The main effect due to factor B is not significant at 1% level of significance.

For interaction effect A and B , F test statistic = 3.51 > 2.97 = critical value , so we reject the null hypothesis.

Conclusion: The effect due to factor interaction of factor A and B is significant at 1% level of significance.

Related Questions

Navigate

• Browse (All)
• Browse M
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.