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Simplified Methods for Statistical Interpretation of Monitoring Data

Authors: Saltzman Be;

Simplified Methods for Statistical Interpretation of Monitoring Data

Abstract

Statistical techniques are useful for interpretation of monitoring data for pollutants, process variables, etc. Simplified nomographical methods are presented for relating numbers of samples to confidence intervals for their mean values, and for determining the proportion of the population exceeding a specified concentration and confidence intervals for the proportion. A chart also is given for design of a sampling program for quality control. Illustrative frequency distribution data are given for hourly-averaged methane concentrations in air over three-week periods. They show trimodal lognormal distributions. These charts are applicable to lognormal distributions, as well as to normal distributions. They are convenient for many common problems.

Related Organizations
Keywords

Quality Control, Air Pollution, Statistics as Topic, Methods

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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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