Literature DB >> 16345678

Bacterial density in water determined by poisson or negative binomial distributions.

A H El-Shaarawi1, S R Esterby, B J Dutka.   

Abstract

The question of how to characterize the bacterial density in a body of water when data are available as counts from a number of small-volume samples was examined for cases where either the Poisson or negative binomial probability distributions could be used to describe the bacteriological data. The suitability of the Poisson distribution when replicate analyses were performed under carefully controlled conditions and of the negative binomial distribution for samples collected from different locations and over time were illustrated by two examples. In cases where the negative binomial distribution was appropriate, a procedure was given for characterizing the variability by dividing the bacterial counts into homogeneous groups. The usefulness of this procedure was illustrated for the second example based on survey data for Lake Erie. A further illustration of the difference between results based on the Poisson and negative binomial distributions was given by calculating the probability of obtaining all samples sterile, assuming various bacterial densities and sample sizes.

Entities:  

Year:  1981        PMID: 16345678      PMCID: PMC243648          DOI: 10.1128/aem.41.1.107-116.1981

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  1 in total

1.  Comparison of eight media-procedures for recovering faecal streptococci from water under winter conditions.

Authors:  B J Dutka; K K Kwan
Journal:  J Appl Bacteriol       Date:  1978-12
  1 in total
  16 in total

1.  Sampling design and enumeration statistics for bacteria extracted from marine sediments.

Authors:  P A Montagna
Journal:  Appl Environ Microbiol       Date:  1982-06       Impact factor: 4.792

2.  Analysis of two-way layout of count data with negative binomial variation.

Authors:  A Maul; A H El-Shaarawi
Journal:  Environ Monit Assess       Date:  1991-01       Impact factor: 2.513

3.  True and false positive rates in maximum contaminant level tests.

Authors:  J Oler
Journal:  Environ Monit Assess       Date:  1991-01       Impact factor: 2.513

4.  Estimation of microbial densities from dilution count experiments.

Authors:  C N Haas
Journal:  Appl Environ Microbiol       Date:  1989-08       Impact factor: 4.792

5.  Methods for Handling Left-Censored Data in Quantitative Microbial Risk Assessment.

Authors:  Robert A Canales; Amanda M Wilson; Jennifer I Pearce-Walker; Marc P Verhougstraete; Kelly A Reynolds
Journal:  Appl Environ Microbiol       Date:  2018-10-01       Impact factor: 4.792

6.  Test of the validity of the Poisson assumption for analysis of most-probable-number results.

Authors:  C N Haas; B Heller
Journal:  Appl Environ Microbiol       Date:  1988-12       Impact factor: 4.792

7.  Microplate fecal coliform method to monitor stream water pollution.

Authors:  A Maul; J C Block
Journal:  Appl Environ Microbiol       Date:  1983-11       Impact factor: 4.792

8.  Some goodness-of-fit methods for the Poisson plus added zeros distribution.

Authors:  A H el-Shaarawi
Journal:  Appl Environ Microbiol       Date:  1985-05       Impact factor: 4.792

9.  Frequency distribution of coliforms in water distribution systems.

Authors:  R R Christian; W O Pipes
Journal:  Appl Environ Microbiol       Date:  1983-02       Impact factor: 4.792

10.  Agreement, precision, and accuracy of epifluorescence microscopy methods for enumeration of total bacterial numbers.

Authors:  Eun-Young Seo; Tae-Seok Ahn; Young-Gun Zo
Journal:  Appl Environ Microbiol       Date:  2010-01-22       Impact factor: 4.792

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