By janet e. l. (editor) ; curtis, gordon d. w. (editor) ; baird, rosamund m. (editor) corry
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Additional resources for Handbook of Culture Media for Food and Water Microbiology
8). e. with Z 95% probability) unless the mean inoculum for each tube contains at least 4 cfu mLÀ1. Even then, because of the eﬀect of the conﬁdence bounds on the probability of obtaining either positive or negative results, a deﬁnitive output can never be certain. e. a response where some tubes show a positive response and others a negative response, in at least one dilution level. 10 shows for a series of ﬁve parallel tubes, the probabilities of obtaining from 0 to 5 positive responses with diﬀerent relative levels of inoculum.
The standard implies that the test can be done either using one pair of plates or by taking a mean count across several plates of each medium; it does not specify the test procedure nor does it impose an upper limit to either count. 50, it does not explain whether or not the ratio is based on any statistical criteria, which implies that they are merely arbitrary values. 1039/9781847551450-00003 Statistical Aspects of the Comparative Evaluation of Microbiological Culture Media 17 A simple w2 procedure can be used to assess whether the diﬀerence in actual cfu counts on parallel plates is statistically signiﬁcant.
G. the likelihood ratio index (G2), which tests the homogeneity of colony counts (for details see Jarvis, 2008). The statistical signiﬁcance of the diﬀerence between mean cfu counts on the test and the reference media can be assessed in various ways. These include parametric tests such as Student’s t-test and the use of conﬁdence intervals, and non-parametric tests such as the Mann–Whitney–Wilcoxon U-test (Wilcoxon, 1945; Mann and Whitney, 1947) and a ‘‘distribution-free’’ w2 test. For parametric tests, if the cfu counts conform to a Poisson distribution, it is necessary ﬁrst to ‘‘normalise’’ the data by taking the square root of each individual value (y ¼ Ox), prior to testing the signiﬁcance of a diﬀerence in the mean values.