Adai, I recently came across the following definition of a statistic which may be relevent to the discussion.
John ----- Berans (2003) provocative definition of statistics as the study of algorithms for data analysis elevates computational considerations to the forefront of the field. It is apparent that the evolutionary success of statistical methods is to a significant degree determined by considerations of computational convenience. As a result,design and dissemination of statistical software has become an integral part of statistical research. from this it follows that a 'Statistic' is " A mathematical function or algorithm for data analysis" -------------------- Duncan Murdoch wrote -------------------- On 11/9/2005 10:01 PM, Adaikalavan Ramasamy wrote: > I think an alternative is to use a p-value from F distribution. Even > tough it is not a statistics, it is much easier to explain and popular > than 1/F. Better yet to report the confidence intervals. Just curious about your usage: why do you say a p-value is not a statistic? Duncan Murdoch Adaikalavan Ramasamy replied ----------------------------- If my usage is wrong please correct me. Thank you. Here are my reason : 1. p-value is a (cumulative) probability and always ranges from 0 to 1. A test statistic depending on its definition can wider range of possible values. 2. A test statistics is one that is calculated from the data without the need of assuming a null distribution. Whereas to calculate p-values, you need to assume a null distribution or estimate it empirically using permutation techniques. 3. The directionality of a test statistics may be ignored. For example a t-statistics of -5 and 5 are equally interesting in a two-sided testing. But the smaller the p-value, more evidence against the null hypothesis. Regards, Adai ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html