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Home > Statistics Every Writer Should Know > The Stats Board > Discusssion

Legal Stats, P-Values
Message posted by Kari (via 209.254.90.38) on December 9, 2001 at 7:52 PM (ET)

Here is a problem posed in one of my law school classes--could anyone help me out? Let me know what you think:

"The following is an old but real case. Evaluate statistically (i.e. the p-value and conclusion)not merely expressing an opinion.
An Alambama court case (Swain v. Alambama) involved a claim of discrimination against blacks in the selection of grand juries. The proportion of blacks in the eligible population was 25%, but only 177 blacks among 1050 were called for jury duty. The court did not find convincing evidence that there was discrimination. Evaluate the following statement that was written by a law professor:
'That trivial differences can appear statistically significant only underscores the admonition that the p-value should not be considered in a vacuum. THe courts are not likely to lose sight of the question of practical significance and to shut their eyes to the possibility that the degree of discrimination [in this case] is itself [minimal].'"

Please, anyone, let me know your views on this, and how you used the p-value to reach your conclusions. Thank you!


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Re: Legal Stats, P-Values
Message posted by JG (via 128.8.23.28) on December 13, 2001 at 10:18 AM (ET)

p-value is one way of doing hypothesis testing. Basically, it is a question of likelihood or probability. For instance, were the jurors selected at random and this is an unusual sample, or were they selected by some legitimate and valid process that 'accidentaly' favors non-blacks, or are blacks more likely than others to not answer a summons to serve, etc. Also, what does the professor think is a 'trivial' difference ? A good example of a trivial difference that may be statistically significant is if the average price of meat at two stores varies by 2 cents. Is this an equivalent problem ? Look at some basic statistics and study binomial populations as well as sampling from a binomial population.



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