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Inferences Based on Observed Frequencies

  • B. L. van der Waerden
Part of the Die Grundlehren der mathematischen Wissenschaften book series (GL, volume 156)

Abstract

In this chapter we are concerned with the same type of problem as in the preceding chapter: the estimation of a parameter ϑ on the basis of observations. In the present chapter we shall restrict attention to observed frequencies h = x/n, where n denotes the number of trials and x the number of times a particular event has occurred. The frequency h is a random variable whose numerator x has a binomial distribution (§ 5). Other than on the known number n, the sample size, the binomial distribution depends only on a single parameter p, the probability of the event. In the case of several events with corresponding observed frequencies th i and probabilities p i , these p i may be either completely unknown or known functions of an unknown parameter ϑ. The problem is to estimate whatever is unknown and to study the reliability of the estimate.

Keywords

Maximum Likelihood Estimate Likelihood Function Asymptotic Distribution Unbiased Estimate Asymptotic Variance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    K. Pearson, On the criterion that a given system of deviations... is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine 50 (1900) p. 157.MATHCrossRefGoogle Scholar
  2. 3.
    F. Bernstein, Z. f. induktive Abstammungs-und Vererbungslehre 37 (1925) p. 236.Google Scholar
  3. 4.
    F. Bernstein, Z. f. induktive Abstammungs-und Vererbungslehre 37 (1925) p. 245.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1969

Authors and Affiliations

  • B. L. van der Waerden
    • 1
  1. 1.Mathematisches InstitutUniversität ZürichSchweiz

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