Expressions for the First Two Moments of the Range of Normal Random Variables with Applications to the Range Control Chart

A common and simple estimate of variability is the sample range, which is the difference between the maximum and minimum values in the sample. While other measures of variability are preferred in most instances, process owners and operators regularly use range (R) control charts to monitor process variability. The center line and limits of the R charts use constants that are based on the first two moments (mean and variance) of the distribution of the range of normal random variables. Historically, the computation of moments requires the use of tabulated constants approximated using numerical integration. We provide exact results for the moments for sample sizes 2 through 5. For sample sizes from 6 to 1000, we used the differential correction method to find Chebyshev minimax rational-function approximations of the moments. The rational function we recommend for the mean (R-chart constant d2) has a polynomial of order two in the numerator and six in the denominator and achieves a maximum error of 4.4 × 10−6. The function for the standard deviation (R-chart constant d3) has a polynomial of order two in the numerator and seven in the denominator and achieves a maximum error of 1.5 × 10−5. The exact and approximate expressions eliminate the need for table lookup in the control chart design phase.

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Publication Details

Journal
Mathematics
Published
2025-05-07
DOI
https://doi.org/10.3390/math13091537
Primary Topic
Advanced Statistical Process Monitoring
Type
article
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article

Expressions for the First Two Moments of the Range of Normal Random Variables with Applications to the Range Control Chart

Don G. Wardell
Mathematics
Advanced Statistical Process Monitoring
article

Expressions for the First Two Moments of the Range of Normal Random Variables with Applications to the Range Control Chart

Don G. Wardell
article en

Abstract

A common and simple estimate of variability is the sample range, which is the difference between the maximum and minimum values in the sample. While other measures of variability are preferred in most instances, process owners and operators regularly use range (R) control charts to monitor process variability. The center line and limits of the R charts use constants that are based on the first two moments (mean and variance) of the distribution of the range of normal random variables. Historically, the computation of moments requires the use of tabulated constants approximated using numerical integration. We provide exact results for the moments for sample sizes 2 through 5. For sample sizes from 6 to 1000, we used the differential correction method to find Chebyshev minimax rational-function approximations of the moments. The rational function we recommend for the mean (R-chart constant d2) has a polynomial of order two in the numerator and six in the denominator and achieves a maximum error of 4.4 × 10−6. The function for the standard deviation (R-chart constant d3) has a polynomial of order two in the numerator and seven in the denominator and achieves a maximum error of 1.5 × 10−5. The exact and approximate expressions eliminate the need for table lookup in the control chart design phase.

MathematicsVol. 13(9)
University of Utah (US)
Openalex Percentile: Top 90%
Advanced Statistical Process Monitoring
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