Analysis of Variance (ANOVA) I
6. ANOVA can not be used to test proposed relationships or predicted correlations between variables in a single group.
This is because ANOVA is tests relationships within various groups and among the groups.
7. If a study had a result of F (2, 147) 4.56, p 0.003, the study had 3 groups and 148 was the sample size.
8. The researchers state that the sample for their study was 28 women with a diagnosis of OA, and that 18 were randomly assigned to the intervention group and 10 were randomly assigned to the control group.
The study strength in the above statement is that the assignment of the treatments to the subjects was random. The weakness is that the treatments were not assigned to the subjects equally.
9. In my opinion the research has established that guided imagery (GI) with progressive muscle relaxation (PMR) reduces pain and decreases mobility difficulties in women with OA. This is because repeated measures ANOVA revealed a significant difference between the two groups in the amount of change in pain and mobility difficulties they experienced over 12 weeks.
10. The possible problems or limitations of this kind of study were that the subjects were old and could have more old-age complications than the ones being studied.
208 EXERCISE 27 • Simple Linear Regression
.= SBP 50.3 0.12x
= SBP 50.3 0.12 (30)
= SBP = 50.3 + 3.6
7. For question 5 SBP is 48.3 while for Question 6 is 53.9
This difference is brought about by the difference in the neonates which give different equations.
DBP = 25.8 0.13 (30)
DBP = 25.8 + 3.9
DBP = 29.7
DBP 30.4 0.11x
DBP 30.4 0.11 (30)
10. DBP 30.4 0.11x
DBP 30.4 0.11 (60)
When postnatal age of 60 hours is used the DBP is greater than when postnatal age of 30 hours is used.
1. The categories were reported to be statistically significant are Medicaid-enrolled, and privately insured
2. The privately insured are statistically significant because the p is 0.001
3. The null hypothesis for marital status (%) is not rejected because it is statistically significant.
4. Two hypotheses were rejected. This is because they were not statistically significant.
5. Education has a greater statistically significant difference among the three groups.
6. There was a significant difference in working status for the three levels of insurance (uninsured, Medicaid enrolled, and privately insured). This is because the statistical value is significant.
7. The level of insurance is not related to gender.
8. The null hypothesis in question 7 should be accepted. This is because the statistical value is not significant.
9. In my own opinion the outcomes of this study is not what I expected.
10. The results of this study should not be generalized to other State Children’s Health Insurance Programs (SCHIPs). This is because different states have different living conditions.
Ott, L.R. & Mendenhall, W. (1994) Understanding statistics,