Abstract
An experimenter threw individually 219 different dice of four different brands and recorded even and odd outcomes for one block of 20,000 trials for each die—4,380,000 throws in all. The resulting data on runs offer a basis for comparing the observed properties of such a physical randomizing process with theory and with simulations based on pseudo-random numbers and RAND Corporation random numbers. Although generally the results are close to those forecast by theory, some notable exceptions raise questions about the surprise value that should be associated with occurrences two standard deviations from the mean. These data suggest that the usual significance level may well actually be running from 7 to 15 percent instead of the theoretical 5 percent.
The data base is the largest of its kind. A set generated by one brand of dice contains 2,000,000 bits and is the first handmade empirical data of such size to fail to show a significant departure from ideal theory in either location or scale.
The analysis was facilitated by a National Science Foundation grant GS-341 and its continuation GS-2044X. It forms part of a larger study of data analysis.
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Iversen, G.R., Longcor, W.H., Mosteller, F., Gilbert, J.P., Youtz, C. (2006). Bias and Runs in Dice Throwing and Recording: A Few Million Throws. In: Fienberg, S.E., Hoaglin, D.C. (eds) Selected Papers of Frederick Mosteller. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-44956-2_25
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