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Applied Statistics for Health Care

Researchers routinely choose a-level of 0.05 for testing their hypotheses. What are some experiments for which you might want a lower a-level (e.g. 0.01)? What are some situations in which you might accept a higher level (e.g. 0.1)? Why?

Suppose you hear an "old-timer" say, "Why, in my day, kids were much more respectful and didn't cause as much trouble as they do nowadays!" Formulate a hypothesis related to this statement that you could test. How would you test it?

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The calculation of a p-value is based on the assumption that a finding is the product of chance alone, given the parameters of a level of significance (for example, choosing a level of significance at 0.05, if your p-value is found to be at 0.05 or lower, then you can conclude with 5% or lower confidence that the results from your experiment were purely due to chance).

In an experiment testing the significance of one's findings, a statistician desires the odds of his/her findings being due merely to chance to be very low. There may be certain situations in which the statistician desires these odds to be even lower than the standard level of significance (i.e. 0.05). A situation in which a higher level may be desired could be when conducting a test on the safety of a new drug. In the world of pharmaceuticals, it is incredibly important that customers are introduced to drugs that are not harmful to them and that, at the most, produce only minor ...

Solution Summary

This solution provides assistance with the hypothesis testing problem attached.

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