### Abstract

Language | English |
---|---|

Pages | 26-28 |

Number of pages | 3 |

Volume | 14 |

Specialist publication | Microbiologist |

Publication status | Published - Dec 2013 |

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### Keywords

- normal distribution
- log-normal distribution
- goodness-of-fit test

### Cite this

*Microbiologist*,

*14*, 26-28.

}

*Microbiologist*, vol. 14, pp. 26-28.

**Statnote 35: are the data log-normal?** / Hilton, Anthony; Armstrong, Richard.

Research output: Contribution to specialist publication › Article

TY - GEN

T1 - Statnote 35: are the data log-normal?

AU - Hilton, Anthony

AU - Armstrong, Richard

PY - 2013/12

Y1 - 2013/12

N2 - In many of the Statnotes described in this series, the statistical tests assume the data are a random sample from a normal distribution These Statnotes include most of the familiar statistical tests such as the ‘t’ test, analysis of variance (ANOVA), and Pearson’s correlation coefficient (‘r’). Nevertheless, many variables exhibit a more or less ‘skewed’ distribution. A skewed distribution is asymmetrical and the mean is displaced either to the left (positive skew) or to the right (negative skew). If the mean of the distribution is low, the degree of variation large, and when values can only be positive, a positively skewed distribution is usually the result. Many distributions have potentially a low mean and high variance including that of the abundance of bacterial species on plants, the latent period of an infectious disease, and the sensitivity of certain fungi to fungicides. These positively skewed distributions are often fitted successfully by a variant of the normal distribution called the log-normal distribution. This statnote describes fitting the log-normal distribution with reference to two scenarios: (1) the frequency distribution of bacterial numbers isolated from cloths in a domestic environment and (2), the sizes of lichenised ‘areolae’ growing on the hypothalus of Rhizocarpon geographicum (L.) DC.

AB - In many of the Statnotes described in this series, the statistical tests assume the data are a random sample from a normal distribution These Statnotes include most of the familiar statistical tests such as the ‘t’ test, analysis of variance (ANOVA), and Pearson’s correlation coefficient (‘r’). Nevertheless, many variables exhibit a more or less ‘skewed’ distribution. A skewed distribution is asymmetrical and the mean is displaced either to the left (positive skew) or to the right (negative skew). If the mean of the distribution is low, the degree of variation large, and when values can only be positive, a positively skewed distribution is usually the result. Many distributions have potentially a low mean and high variance including that of the abundance of bacterial species on plants, the latent period of an infectious disease, and the sensitivity of certain fungi to fungicides. These positively skewed distributions are often fitted successfully by a variant of the normal distribution called the log-normal distribution. This statnote describes fitting the log-normal distribution with reference to two scenarios: (1) the frequency distribution of bacterial numbers isolated from cloths in a domestic environment and (2), the sizes of lichenised ‘areolae’ growing on the hypothalus of Rhizocarpon geographicum (L.) DC.

KW - normal distribution

KW - log-normal distribution

KW - goodness-of-fit test

UR - http://issuu.com/societyforappliedmicrobiology/docs/dec2013_micro

M3 - Article

VL - 14

SP - 26

EP - 28

JO - Microbiologist

T2 - Microbiologist

JF - Microbiologist

SN - 1479-2699

ER -