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Examples ofsampling distribution
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Unfortunately, the functional form of an estimated eigenvalue'ssamplingdistributionis unknown, and it is even impossible to calculate its standard error analytically.
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So our null hypothesis implies a certainsamplingdistributionfor the percentage of successes.
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That is, while the bootstrap estimate of the entiresamplingdistributionis available, the normal approximation only uses its standard deviation.
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The normality assumption is required for hypothesis testing and particularly to establish thesamplingdistributionof test statistics.
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The third level of analysis involves the determination of the confidence interval on the basis of the empiricalsamplingdistribution.
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To recapitulate (1), every application of the t-test evokes the appropriatesamplingdistributionof differences.
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Thesamplingdistributionof linkage disequilibrium under an infinite allele model without selection.
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Bootstrapping allows the estimation of thesamplingdistributionof virtually any statistic, merely by re-sampling and re-estimating it multiple times.
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In this way, thesamplingdistributioncan be estimated experimentally, without any a priori assumptions about its functional form.
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The above computations were repeated 20,000 times to obtain thesamplingdistributionfor the direction selectivity index, under the null hypothesis that there was no direction selectivity.
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The point estimation of a parameter is always a much easier mathematical problem to solve than assessing the estimator'ssamplingdistributionand using it to make inferences.
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They do not state thesamplingdistributionof their estimated correlation.
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Then, permutation tests performed on the data allow the computation of the corresponding nullsamplingdistribution.
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This distribution is not necessarily normal in the same sense that thesamplingdistributionof a sample mean is normal as a consequence of the central limit theorem of statistics.
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When they are tabulated in the form of a frequency distribution, the result is an empirical approximation to the randomsamplingdistributionof the differences between two sample means.
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Thesamplingdistributionof disease-associated alleles.
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These coefficient estimates will therefore have asamplingdistributionbased on the generating algorithm and the estimator being used, and we are interested in the properties of these distributions.
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When sample distributions were examined, the skewness in the samples was found to be sufficiently low to indicate normality for thesamplingdistributionof the mean (4).
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Thesamplingdistributiondepends on the underlying distribution of the population, the statistic being considered, the sampling procedure employed, and the sample size used.
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This example is from Wikipedia and may be reused under a CC BY-SA license.
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This example is from Wikipedia and may be reused under a CC BY-SA license.These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors.
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