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In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement, is known, in the English-speaking world, as the German tank problem, due to its application in World War II to the estimation of the number of German tanks. The analyses illustrate the difference between frequentist inference and Bayesian inference.

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  • German tank problem
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  • In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement, is known, in the English-speaking world, as the German tank problem, due to its application in World War II to the estimation of the number of German tanks. The analyses illustrate the difference between frequentist inference and Bayesian inference.
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  • In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement, is known, in the English-speaking world, as the German tank problem, due to its application in World War II to the estimation of the number of German tanks. The analyses illustrate the difference between frequentist inference and Bayesian inference. Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.
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