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Some Useful Moment Results in Sampling Problems
by
O'Neill, B.
in
Analysis of covariance
/ Confidence interval
/ Covariance
/ Degrees of freedom
/ Estimating techniques
/ Estimation
/ Estimators
/ Expectations
/ Finite population correction
/ Kurtosis
/ Mathematical moments
/ Population
/ Population mean
/ Population moments
/ Random sampling
/ Ratio of nested variance estimators
/ Sample mean
/ Sample moments
/ Sampling
/ Skewed distribution
/ Statistical variance
/ Statistics
/ Variance estimator
/ Variances
2014
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Some Useful Moment Results in Sampling Problems
by
O'Neill, B.
in
Analysis of covariance
/ Confidence interval
/ Covariance
/ Degrees of freedom
/ Estimating techniques
/ Estimation
/ Estimators
/ Expectations
/ Finite population correction
/ Kurtosis
/ Mathematical moments
/ Population
/ Population mean
/ Population moments
/ Random sampling
/ Ratio of nested variance estimators
/ Sample mean
/ Sample moments
/ Sampling
/ Skewed distribution
/ Statistical variance
/ Statistics
/ Variance estimator
/ Variances
2014
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Do you wish to request the book?
Some Useful Moment Results in Sampling Problems
by
O'Neill, B.
in
Analysis of covariance
/ Confidence interval
/ Covariance
/ Degrees of freedom
/ Estimating techniques
/ Estimation
/ Estimators
/ Expectations
/ Finite population correction
/ Kurtosis
/ Mathematical moments
/ Population
/ Population mean
/ Population moments
/ Random sampling
/ Ratio of nested variance estimators
/ Sample mean
/ Sample moments
/ Sampling
/ Skewed distribution
/ Statistical variance
/ Statistics
/ Variance estimator
/ Variances
2014
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Journal Article
Some Useful Moment Results in Sampling Problems
2014
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Overview
We consider the standard sampling problem involving a finite population of N objects and a sample of n objects taken from this population using simple random sampling without replacement. We consider the relationship between the moments of the sampled and unsampled parts and show how these are related to the population moments. We derive expectation, variance, and covariance results for the various quantities under consideration and use these to obtain standard sampling results with an extension to variance estimation with a \"finite population correction.\" This clarifies and extends standard results in sampling theory for the estimation of the mean and variance of a population.
Publisher
Taylor & Francis,AMERICAN STATISTICAL ASSOCIATION,American Statistical Association
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