This article will be permanently flagged as inappropriate and made unaccessible to everyone. Are you certain this article is inappropriate? Excessive Violence Sexual Content Political / Social
Email Address:
Article Id: WHEBN0026297705 Reproduction Date:
In the design of experiments in statistics, the lady tasting tea is a famous randomized experiment devised by Ronald A. Fisher and reported in his book The Design of Experiments (1935).[1] The experiment is the original exposition of Fisher's notion of a null hypothesis.[2][3] Fisher's description is less than 10 pages in length and is notable for its simplicity and completeness regarding terminology, calculations and design of the experiment.[4] The example is loosely based on an event in Fisher's life. The lady in question was Muriel Bristol, and the test used was Fisher's exact test.
The lady in question claimed to be able to tell whether the tea or the milk was added first to a cup. Fisher proposed to give her eight cups, four of each variety, in random order. One could then ask what the probability was for her getting the number she got correct, but just by chance.
If and only if the Lady properly categorized all 8 cups was Fisher willing to reject the null hypothesis – effectively acknowledging the Lady's ability at a 1.4% significance level (but without quantifying her ability). Fisher later discussed the benefits of more trials and repeated tests.
David Salsburg[5] reports that a colleague of Fisher, H. Fairfield Smith, revealed that in the test, the woman got all eight cups correct.[6] The chance of someone who just guesses getting all correct, assuming she guesses that four had the tea put in first and four the milk, would be only 1 in 70 (the combinations of 8 taken 4 at a time).
In popular science, Salsburg published a book entitled The Lady Tasting Tea,[5] which describes Fisher's experiment and ideas on randomization. Deb Basu wrote that "the famous case of the 'lady tasting tea'" was "one of the two supporting pillars ... of the randomization analysis of experimental data".[7]
Probability theory, Regression analysis, Mathematics, Observational study, Calculus
MythBusters, Richard Dawkins, Stephen Hawking, Science, Carl Sagan
Statistics, Multivariate statistics, Survival analysis, Epidemiology, Bioinformatics
Statistics, England, Gonville and Caius College, Cambridge, Lady tasting tea, Design of experiments
Statistics, Null hypothesis, Statistical inference, Bayesian inference, Decision theory
Statistics, Design of experiments, Effect size, Regression analysis, Evolutionary biology