Published online by Cambridge University Press: 10 September 2012
Results for a total of 804 double-blind tastes by experienced tasters during nine tasting events are reported. T-test results reject the hypothesis that flight-position bias affects results. The distribution of ranks for a wine is a mixture distribution, and tests concerning the variance of that mixture distribution do not isolate the variance due to the randomness mixture component alone. T-statistics for the mean ranks of high- and low-ranking wines are over several standard deviations from a random expectation. T-tests show that the statistical significance of the difference between wine ranks is positively related to the difference in their mean ranks. At a 95% level of significance, the difference in ranks between the first- and second-place wines appears to be significant in 33% of tastings. At 95%, the difference in ranks between the first- and last-place wines appears to be significant in 100% of tastings. Monte Carlo simulation shows that much of those differences could be illusory and due to ranking procedures that lead to Type I errors. While the mean correlation coefficient between price per bottle and mean preference is a weakly positive 0.23, this may not indicate an inefficient market. (JEL Classifications: A10, C00, C12, D12)
I am grateful to the late professor George Kuznets at the University of California at Berkeley for his patience with me in statistics classes, Professor Emeritus Bert Mason of California State University at Fresno for his ideas and guidance during fieldwork and to an anonymous reviewer for insightful suggestions.