Application of binomial distributions to quality assurance of quantitative chemical analyses

Friedman, Linda C.; Bradford, Wesley L.; Peart, Dale B.

doi:10.1080/10934528309375123

Cited by 10 publications

(5 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Measures of precision were determined from the control chart data by applying binomial-probabilitydistribution procedures described by Friedman, Bradford, and Peart (1983) and by Peart and Thomas (1983a). The precision evaluation is based on whether or not an analytical method could produce results within ± 2 standard deviations of the MPV.…”

Section: Binomial-probability-distribution Technique To Assess Precisionmentioning

confidence: 99%

Quality-assurance results for routine water analyses in US Geological Survey laboratories, water year 1997

1999

View full text Add to dashboard Cite

Positive analytical bias throughout the reference sample range was indicated for aluminum (whole-water recoverable, inductively coupled plasma-atomic emission spectrometry), and a negative analytical bias throughout the reference sample range was indicated for barium (whole-water recoverable, inductively coupled plasma-atomic emission spectrometry). As with the National Water Quality Laboratory, the Quality of Water Service Unit had very few nutrient sample biases.

show abstract

Section: Binomial-probability-distribution Technique To Assess Precisionmentioning

confidence: 99%

Quality-assurance results for routine water analyses in US Geological Survey laboratories, water year 1997

1999

View full text Add to dashboard Cite

show abstract

“…Points outside the range of the plots are forced to appear at the limit (dt6 standard deviations), with the actual number of standard deviations indicated adjacent to the point (see figure 1, for example). Precision and bias are determined by applying binomial-probability-distribution equations to the data using procedures described by Friedman, Bradford, and Peart, (1983); and by Peart and Thomas, (1983a). When preci¬ sion is determined using these procedures, it contains an element of bias because MPV's, rather than analyzed means, are used as the basis for determining the number of standard deviations each constituent deviates from that value.…”

Section: Statistical Evaluationmentioning

confidence: 99%

Quality-assurance data for routine water analysis in the National Water-Quality Laboratory of the U.S. Geological Survey for water year 1987 /

Lucey¹,

Peart²

1989

Self Cite

View full text Add to dashboard Cite

The U.S. Geological Survey maintains a quality-assurance program based on the analysis of reference sam¬ ples for its National Water-Quality Laboratory located in Denver, Colorado. Reference samples containing selected inorganic constituents are prepared at the Survey's Water Quality Services Unit in Ocala, Florida, disguised as rou¬ tine samples, and sent daily or weekly, as appropriate, to the laboratory through other Survey offices. Nutrient sam¬ ples and precipitation samples also were submitted as samples of unknown concentration. The results are stored permanently in the National Water Data Storage and Retrieval System (WATSTORE), the Survey's data base for all water data. These data are analyzed statistically for precision and bias. The results of these statistical analyses are discussed for data collected during water-year 1987. An overall evaluation of the major and trace constituent data for water-year 1987 indicated a lack of precision in the National Water-Quality Laboratory for the determination of 6 out of 58 constituents: chloride; chromium; iron, total recoverable; zinc, dissolved (atomic absorption spectroscopy); zinc, (inductively coupled plasma emission spectroscopy); and zinc, total recoverable. There were fewer constituents having positive or negative bias during water-year 1987 than during water-year 1986. A lack of precision was indicated in the determination of three of the six nutrient constituents: nitrate + nitrite nitrogen as N, orthophosphate as R and phosphorus as R A biased condition was indicated in the determination of ammonia + organic nitrogen as N. There was acceptable precision in the determination of all 10 precipitation-level constituents. One precipita¬ tion-level constituent, sodium, indicated a biased condition.

show abstract

“…Measures of precision were determined from the control chart data by applying binomialprobability-distribution procedures described by Friedman, Bradford, and Peart (1983) and by Peart and Thomas (1983a). The precision evaluation is based on whether or not an analytical method could produce results within ±2 standard deviations of the MPV.…”

Section: Binomial-probability-distribution Technique To Assess Precisionmentioning

confidence: 99%

Quality-assurance results for routine water analyses in U.S. Geological Survey laboratories, water year 1998

Ludtke¹,

Woodworth²,

Marsh³

2000

View full text Add to dashboard Cite

Application of binomial distributions to quality assurance of quantitative chemical analyses

Cited by 10 publications

References 1 publication

Quality-assurance results for routine water analyses in US Geological Survey laboratories, water year 1997

Quality-assurance results for routine water analyses in US Geological Survey laboratories, water year 1997

Quality-assurance data for routine water analysis in the National Water-Quality Laboratory of the U.S. Geological Survey for water year 1987 /

Quality-assurance results for routine water analyses in U.S. Geological Survey laboratories, water year 1998

Contact Info

Product

Resources

About