While the normal or Gaussian distribution is frequently applied in biostatistics and modeling, many biological phenomena are better characterized by alternative distributions such as power laws or skewed models, meaning they do not consistently follow Gaussian statistics.
Evidence for · 3
Copula Gaussian graphical modelling of biological networks and Bayesian inference of model parameters
2019 · cited by 8
Paper 1 uses Copula Gaussian graphical models to successfully represent complex biological networks and datasets.
Evidence against · 5
Coupling Power Laws Offers a Powerful Modeling Approach to Certain Prediction/Estimation Problems With Quantified Uncertainty
2022 · cited by 5
Paper 3 notes that power law distributions frequently fit natural and biological data exceptionally well when the Gaussian distribution fails.
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More for · 2
Gaussian Distribution Model for Detecting Dangerous Operating Conditions in Industrial Fish Farming
2021 · cited by 7
Paper 2 demonstrates a Gaussian distribution model for monitoring biological and chemical systems in aquaculture.
Escape from omnishambles in statistics: back to the basics
2015 · cited by 0
Paper 8 notes that many biological phenomena and biostatistics are traditionally modeled using normal distributions.
More against · 4
Coupling Power Laws Offers a Powerful Method for Problems such as Biodiversity and COVID-19 Fatality Predictions
2021 · cited by 5
Paper 4 states that power law distributions are often found to fit biological data when normal distributions fail.
The Log-Gamma Distribution and Non-Normal Error
2021 · cited by 1
Paper 5 shows that biological or actuarial error terms are frequently skewed and non-Gaussian.
The time distribution of biological phenomena – illustrated with the London marathon
2018 · cited by 1
Paper 6 points out that existing standard distributions are often inappropriate for biological phenomena because biological dynamics possess unique statistical properties.
clrDV: a differential variability test for RNA-Seq data based on the skew-normal distribution
2022 · cited by 0
Paper 11 utilizes a skew-normal distribution to model RNA-Seq gene counts, demonstrating that non-standard distributions are needed for biological variability.