Ditching the norm: Using alternative distributions for biological data analysis

Most classical statistical tests assume data are normally distributed. If this assumption is not met, researchers often turn to non-parametric methods. These methods have some drawbacks, and if no suitable non-parametric test exists, a normal distribution may be used inappropriately instead. A better option is to select a distribution appropriate for the data from dozens available in modern software packages. Selecting a distribution that represents the data generating process is a crucial but overlooked step in analysing data. This paper discusses several alternative distributions and the types of data that they are suitable for.

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Publication Details

Journal
Laboratory Animals
Published
2024-08-19
DOI
https://doi.org/10.1177/00236772241246602
Citations
1
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
0.71
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article

Ditching the norm: Using alternative distributions for biological data analysis

Stanley E. Lazic
1 citations
Laboratory Animals
Statistical Methods in Clinical Trials
0.71
article

Ditching the norm: Using alternative distributions for biological data analysis

Stanley E. Lazic
article en
1 citations

Abstract

Most classical statistical tests assume data are normally distributed. If this assumption is not met, researchers often turn to non-parametric methods. These methods have some drawbacks, and if no suitable non-parametric test exists, a normal distribution may be used inappropriately instead. A better option is to select a distribution appropriate for the data from dozens available in modern software packages. Selecting a distribution that represents the data generating process is a crucial but overlooked step in analysing data. This paper discusses several alternative distributions and the types of data that they are suitable for.

Laboratory AnimalsVol. 58(5)
Prioris.ai (Canada) (CA)
Openalex Percentile: Top 27%
Statistical Methods in Clinical Trials
0.71
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