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In a clinical trial cluster sampling could be used to select individuals from a similar geographic area.
19-a

20-B

21-B

22-C

23-B

24-C

25-B

26-B

27-B

28-C

29-a

30-a

31-a

32-a

33-a

34-a

35-B

Quiz 2

1-True

2-False

3-True

4-False

5-False

6-True

7-True

8-False

9-True

10-False

11-True

12-True

13-False

14-False

15-False

16-B

17-D

18-C

19-a

20-D

21-C

22-B

23

H0 is the null hypothesis and it generally states that there is no difference or no change. H1 is the alternative hypothesis or the researcher hypothesis and is generally the opposite of the null hypothesis. Hypothesis testing centers on the acceptance and rejection of the null hypothesis.

24.

In most clinical research studies the researcher would use a one-tailed test. This is so for two basic reasons the first is that one tailed tests are more powerful and the second is that theoretically the researcher is usually aware of the direction in which the change is expected...

This level of significance is appropriate because you would want to ensure that the treatment is actually working. A lower level of significance would mean a higher risk of rejecting the null when it is true (Aron, Coups & Aron 2011). This would mean a greater risk of putting a product on the market that does not work. .05 is too high a risk to take, for replacing the standard treatment.

26

The alpha level for this would be 0.05. This alpha level is adequate because the outcome of a type one error would not be dire. The probability of rejecting the null when the null is true would be only 5% and the issue here does not warrant a more stringent approach.

27.

Step 1 Ho Mu=200

H1 Mu > 200

Step 2

The alpha level would be 0.05

T=1.66

Step 3

Conduct a one sample t-test

One Tailed test

Xbar-X/s/Square root n

217-200/39/sqt 100

17/3.9

t=4.36

df=99

Step 4

Compare tobs to t crit

4.36 is larger than 1.66

We therefore reject the null hypothesis

Conclusion- the serum levels in the sample is of concern, it is significantly higher than normal.

28

Step 1

Hu-Mu=200

H1-Mu

Aron, a., Coups E.J. & Aron E.N. (2011). Statistics for the behavioral and social sciences:

A brief course. New York NY Prentice Hall.

Creswell J.W. (1994).Research Design: Qualitative and Quantitative approaches. London: Sage

Publications

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We have also talked about the "blue print" of a study, or the logical model of proof which guides the researcher throughout the entire study -- i.e. The research design. It is by which the investigator determines the relationships between variables being tested. We have discussed true experiments, its nature and validity issues as well as quasi-experimental designs. We also provided a discussion of the difference between these two designs. What

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The literature review discussed risk factors for drop out extensively and presented studies that investigated risk factors for drop out. However, the research design did not clearly tie this research to the study examined by Dennison. Students considered at-risk were chosen by the school and proper parental consent was obtained. It is not known how at risk students were chosen. Therefore, it cannot be determined it sample bias existed in