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.
Authors
- Stanley E. Lazic (ORCID: https://orcid.org/0000-0002-3409-3407)
Institutions
- Prioris.ai (Canada) (CA)
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