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A fundamental ethical problem in statistics

Question

A fundamental ethical problem in statistics arises in experimentation (i.e., in the context of studies of

experimental drugs for treating AIDS). On one side, organizations such as the National Institute of Health insist on randomly assigning treatments such as flipping a coin for each patient to decide which treatment to assign. The advantage of randomized experiments is that they allow reliable conclusions without the need to worry about lurkingvariables. However, some groups of AIDS patients have opposed randomization, instead making the argument that each patient should be assigned the best available treatment (or to be more precise, whatever treatment is currently believed to be the best). The ethical dilemma is to balance the benefits to the patients in the study (who would like the opportunity to choose among available treatments) with future patients (who would be served by learning as soon as possible about the effectiveness of the competing treatments). The issue is complicated. On one hand, the randomized study is most trustworthy if all the patients in the study participate. If they are not treated respectfully, the patients might go outside the study and try other drugs, which could bias the estimates of treatment effects. On the other hand, the patients might benefit from being in an experimental study. Even if the treatment is randomized, the patients are getting close medical attention from the researchers. Current best practice is to design studies so that all subjects will be expected to benefit in some way, but still keeping the randomized element. For example, a study can compare two potentially beneficial experimental treatments, rather than comparing a treatment to an inert “control.” However, there will always be conflicts of interest between the patients in the study, the scientists conducting it, and the public at large. In your original post, compare and contrast at least two research designs that might be used to research life threatening diseases/disorders. At least one design should present ethical issues and at least one design should minimize potential ethical issues. Provide at least one Scripture passage that supports your ethical perspectives on medical/public health research.

 
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Cummulative frequency

Question

Cummulative frequency: what is the steps in finding the media and the inter-quartile range of grouped data.

 
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A small pilot study

Question

A small pilot study is conducted to investigate the effect of a nutritional supplement on total body weight. Six

participants agree to take the nutritional supplement. To assess its effect on body weight, weights are measured before starting the supplementation and then after 6 weeks. The data are shown below. Is there a significant increase in body weight following supplementation?

Use a paired t-test at a 5% level of significance.

1. df=

2. Critical Value=

3. Computed statistic=

4. Based on comparing the computed statistic to the critical value which of the following

is (are) true? (4 points)

a. There is significant evidence, alpha=0.05, to show that body weight increased

following supplementation?

b. There is not significant evidence, alpha=0.05, to show that body weight increased

following supplementation?

c. Statistically speaking the difference in initial weights and weights after 6 weeks is 0.

d. b and c

Subject Initial Weight Weight after 6 Weeks

1 155 157

2 142 145

3 176 180

4 180 175

5 210 209

6 125 126

 
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Average adult Americans are about one inch taller

Question

Average adult Americans are about one inch taller, but nearly a whopping 25 pounds heavier than they were in 1960,

according to a new report from the Centers for Disease Control and Prevention (CDC). The bad news, says the CDC is that average BMI has increased among adults from approximately 25 in 1960 to 28 in 2002. Boston is considered one of America�s healthiest cities – is the weight gain since 1960 similar in Boston? A sample of n=25 adults suggested a mean increase of 17 pounds with a standard deviation of 8.6 pounds. Is Boston statistically significantly different in terms of weight gain since 1960? Apply the appropriate test at a 5% level of significance.


1)critical t value: +/-

2)Computed statistic:

Based on comparing the computed statistic to the critical value which of the following is (are) true?

a)There is significant evidence, alpha=0.05, that the BMI for Boston residents is significantly different than 25.

b)There is not significant evidence, alpha=0.05, that the BMI for Boston residents is significantly different than 25.

c)Statistically speaking the difference between the BMI for Boston residents and a BMI of 25 is 0

d) b and c

 
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