An Improved Range Estimator of Sigma for Determining Sample Sizes

Rhiel, Steven G.

doi:10.1080/03610918908812822

Cited by 5 publications

(2 citation statements)

References 10 publications

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“…Table 1 contains the standardized mean ranges simulated from the distributions with infinite ranges for sampling frame sizes from 500 to 1,000,000. By dividing d n into the range of a sampling frame, an unbiased estimate of σ is obtained (i.e., E ( R / d n ) = σ) and would be useful in determining σ when a sample size is desired (Rhiel, 1989).…”

Section: Resultsmentioning

confidence: 99%

“…Cochran (1977) suggests dividing the range by 2 if the population is V-shaped, by 3.47 if it is rectangular, by 4.22 if it is shaped like a right triangle, and by 4.88 if it is shaped like an isosceles triangle. Rhiel (1989) developed standardized mean ranges which could be divided into the range of a sampling frame to estimate s for determining sample sizes. Browne (2001) provides range divisors that give you a 95% chance of getting an estimate greater than or equal to s.…”

Section: Introductionmentioning

confidence: 99%

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An Update on Using the Range to Estimate σ When Determining Sample Sizes

Rhiel

Markowski

2017

Psychol Rep

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In this research, we develop a strategy for using a range estimator of σ when determining a sample size for estimating a mean. Previous research by Rhiel is extended to provide d values for use in calculating a range estimate of σ when working with sampling frames up to size 1,000,000. This allows the use of the range estimator of σ with "big data." A strategy is presented for using the range estimator of σ for determining sample sizes based on the d values developed in this study.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Update on Using the Range to Estimate σ When Determining Sample Sizes

Rhiel

Markowski

2017

Psychol Rep

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Using the Sample Range as a Basis for Calculating Sample Size in Power Calculations

Browne

2001

The American Statistician

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Using the Range to Calculate the Coefficient of Variation

Rhiel

2004

Psychol Rep

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In this research a coefficient of variation (CVhigh-low) is calculated from the highest and lowest values in a set of data. Use of CVhigh-low when the population is normal, leptokurtic, and skewed is discussed. The statistic is the most effective when sampling from the normal distribution. With the leptokurtic distributions, CVhigh-low works well for comparing the relative variability between two or more distributions but does not provide a very "good" point estimate of the population coefficient of variation. With skewed distributions CVhigh-low works well in identifying which data set has the more relative variation but does not specify how much difference there is in the variation. It also does not provide a "good" point estimate.

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An Improved Range Estimator of Sigma for Determining Sample Sizes

Cited by 5 publications

References 10 publications

An Update on Using the Range to Estimate σ When Determining Sample Sizes

An Update on Using the Range to Estimate σ When Determining Sample Sizes

Using the Sample Range as a Basis for Calculating Sample Size in Power Calculations

Using the Range to Calculate the Coefficient of Variation

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