Homework #1 Statistical Concepts Name:___Richard Beck BIO/BTEC180 Biostatistics MiraCosta College

Example 1: Dolphin Therapy?1. Why did the researchers include a comparison group in this study? Why didn’t they just see how many patients

showed substantial improvement when given the dolphin therapy? TThe comparison group acts as a control. They are given as a reference value to compare for your null hypothesis. If there was no group to compare against it would be impossible to tell if they got better because of the dolphins or some other external influence.

2. Why do you think patients with mild to moderate depression only were allowed to participate?It could be dangerous for patients with extreme depression to be that far ourside of thier surroundings or be weaned off medication.

3. Do you think the age range is important?The age range is important. For it to be more significant it should be focused on narrower age range to tell if the results only impact certain groups. For instance perhaps the unresponsive people in the sudy were only old or only young. It would be impossible to well without a smaller age range.

4. Why the “random assignment” when they got to the island? They were randomized to prevent bias from influencing the results of the study. Randomizing helps make sure the results are accurate and only because of the experimental infleunce.

5. Do the data appear to support the claim that dolphin therapy is effective? A useful first step is to calculate the proportion who improved in each group. Calculate these proportions. Did the dolphin therapy group have a higher proportion who showed substantial improvement than the control group?Dolphin group= 10 / 15 had improvement (67% Improvement) Control= 3/12 showed improvement (25% Improvement)Yes the dolphin group had higher proportions of improvement 67% vs 25%. The data appears to support the idea that the dolphin group has greater improvement.

6. How would you describe the results of the simulation? That is, how would you describe what the results looked like. Think about the shape, where it’s centered, how spread out the data is. Draw a picture if it helps.The simulation showed that the probablility of having a random improvement similar to the results was not improbable and likely happened as a result of random chance rather than the result of a significant improvement. The P value of the simulation did not show significance and did not disprove the null hypothesis. The graph showed a bell curve shape with the data centered between the points of 4 and 9. It tapered quickly

off on both extremes.

Example 2: Contagious Yawns?1. Do the data appear to support the claim that yawns are contagious?

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Dolphin Improvers

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Mean 6.505StDev 1.383N 10000

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Histogram of Dolphin ImproversNormal

The data from the small smaple size shows that it has a slightly higher proportion of yawns than the control group.

2. Calculate the proportion of yawners for each group. Did the “yawn seed” group have a higher proportion of yawners, as compared to the control group?

Seed group = 10/34 yawned = 29% Control group = 4/16 = 25Yes, the seed group had a slightly higher proportion of yawns compared to the control.

3. Is it possible that yawning is not contagious, and random assignment alone is responsible for the observed difference in proportions of yawners between the two groups? (This is what The Skeptic would say.)Yes, it is possible and likely that the seed group’s higher proportion was due only to random assignment rather than a significant effect.

4. What were the results of the in-class re-sampling simulation?

The results in resampling were that the effect of the seed yawning was not significant and did not discprove the null hypothesis. The seed yawning group did not exhibit a significant ammount of yawning compared to the control group (p=0.51).

Example 3: Leaning While Kissing?1. Based on the in-class re-sampling simulation results, would you conclude that the researchers’ data (8 of 12

couples leaning to the right) provides strong evidence that couples really do tend to the lean to the right more often than the left? Explain the reasoning behind your answer.

I would not conclude that there is enough evidence to say that couples tend to lean to the right more than the left. The difference between the two groups is small and the sample size is small. The experiement does not have enough pwer.

2. Based on the second re-sampling results, would you conclude that the researchers’ data (80 of 124 couples leaning to the right) provides strong evidence that couples in general really do tend to the lean to the right more often than the left?

Yes the second re-sampling results show significance to the experimental hypothesis (p=0.0009) that couples are more “inclined “ to lean to the right when they are kissing.

3. Why do we get such different results if the proportion (about 2 out of 3) of people leaning to the right is the same?

The results of the the two experiments are so different, even though they have the same proprotion, is because the second sample size was much bigger than the first. This gives the second experiment much more power and less probablity that the results were due to random probability.

Example 4: EPO for Neuropathy1. What’s a clinical trial? What are the phases?2. What two characteristics of a medicinal therapy do companies need to demonstrate to get FDA approval?3. With respect to the question above, what can we conclude about EPO for the treatment of peripheral

neuropathy?

Example 5: EPO for tissue protection following CABG1. Explain why the difference in proportions favoring the treatment is basically the same as in the EPO trial for

neuropathy and yet we come to very different conclusions. For example, in the first trial, there was a 23 percentage difference favoring the treatment and, in the CABG trial, there was 21 percentage difference favoring the treatment.