final Assignment Statistics

# final Assignment Statistics - Running head Final Exam 1...

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Running head: Final Exam 1 Final Exam Name: Richard Steele Instructor: Stacey Thompson Course: PSY325: Statistics for the Behavioral & Social Sciences (PSI1608A) Date: March 17, 2016

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Final Exam 2 Essay 1 The null hypothesis is that there is no relationship or difference between the treatments, but the alternative hypothesis is that there is some difference. Since p=.0008 which are less than the level of significance alpha=.05, so the results are statistically significant. The researchers that would do this study would reject it because it is an invalid theory. On the off chance that the invalid speculation was genuine, an example with results like this would just happen eight out of 10,000 trials. This would be hard to relate to a sample test. Along these lines, we would trust that the null hypothesis was wrong. The sample is large enough, but we are not told what the population is. Are the participants Chinese or American? Are they adults or children? Are they Male or female? Assuming the samples are truly randomly chosen from a well-defined population the sample seems adequate. Conceivable confinements incorporate a badly characterized population, and the determination of the example is not entirely random. Additionally, the examination couldn't be double-blind because it is difficult to mask whether you are getting a shot or the fog. There is no control group to characterize the probability of an unvaccinated individual getting seasonal flu, however, this may be known for the given population. Was this sort of flu considered? Were the participants presented to a specific strain or would they say they were prone to get that certain kind of flu because this season's cold virus reported a certain strain of the flu? First, we have to identify any problems in the first test such as the right kind of population and fix that. Make sure to look for any confusing variables including flu strain, age, and health of participants. Also, make sure the experiment is double-blind by including a control group who have issued a placebo (salt-water spray shot nothing medical in it to reduce the placebo/nocebo effects or give everyone two different treatments one placebo and the other of the actual treatment. Give us a chance to accept that the study results are right. It gives the idea that getting the antibody as a shot is more successful than through nasal application. Be that as it may, we are not told what the rate of untreated individuals who might get this season's cold virus is. Assume 1/4 of untreated individuals presented to this season's cold virus really ended up tainted. (So 125 out of 500.) Then the little point of preference of nasal security won't be justified regardless of the time and cost. In fact, while the contrast in the middle of shot and fog may be measurably critical, the outcomes won't be essentially noteworthy in that the cost, time, and money will not exceed the advantage such as fewer people getting the flu. For the situation of
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• Spring '16
• Stacey Thompson
• Null hypothesis, Statistical hypothesis testing, Statistical significance, research study critique, Statistical power, Finn

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