Cochran's rule for simple random sampling

Cochran's rule for simple random sampling

Cochran's rule for the minimum sample size to ensure adequate coverage of nominal 95% confidence intervals is derived by using the Edgeworth expansion for the distribution function of the standardized sample mean. The rule is extended for confidence intervals based on the Studentized sample mea...

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Veröffentlicht in:Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2000, Vol.62 (4), p.787-793
Hauptverfasser: Sugden, R. A., Smith, T. M. F., Jones, R. P.
Format: Artikel
Sprache:eng
Schlagworte:
Approximation
Confidence interval
Coverage probability
Data analysis
Distribution
Edgeworth expansion
Exact sciences and technology
Kurtosis
Mathematics
Nonparametric inference
Parametric inference
Population mean
Population size
Probabilities
Probability and statistics
Random sampling
Sample mean
Sample size
Sampling
Sampling distributions
Sampling fraction
Sampling theory, sample surveys
Sciences and techniques of general use
Simple random sampling
Simulation
Skewness
Statistical methods
Statistical variance
Statistics
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Beschreibung
Zusammenfassung:Cochran's rule for the minimum sample size to ensure adequate coverage of nominal 95% confidence intervals is derived by using the Edgeworth expansion for the distribution function of the standardized sample mean. The rule is extended for confidence intervals based on the Studentized sample mean. The performance of the rule and Edgeworth approximations for smaller sample sizes are examined by simulation.
ISSN:1369-7412
1467-9868
DOI:10.1111/1467-9868.00264