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Author: Julie McCormick 900 W. Shore Rd. Phone: 516-625-4848 Because the reliability of a relationship is not an intuitive concept we depend on statistical procedures to test if a sample is representative of the population. But this is also not intuitive. It would be intuitive if we could use maps to demonstrate our representativeness. For example, in map A we suspect that the identified breast cancer sufferers are representative of breast cancer sufferers in the USA because they appear to be widely dispersed yet concentrated in known population centers. We also suspect the sample should be representative because it was drawn from a representative panel of 250,000 househlds. However, the intuitive map and representative panel are not adequate because it is possible that breast cancer sufferers are not distributed uniformly throughout the population. We need to accompany the map with an acceptable statistical measure of representativeness and confirm that the breast cancer sufferers found in our specific sample represent the entire population. In other words, how probable would it be that a similar group of sufferers would be found if another sample was drawn from the same population. We are not interested only in what is going on in our sample; we are interested in the sample only to the extent that it can provide information about the population. If the sample meets specific criteria, then the reliability of a relationship between variables observed in our sample can be quantitively estimated and represented using a standard measure (p-value or statistical significance level). |
