Related Experiment Video
Updated: Jun 4, 2026

A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances
Published on: October 10, 2020
Influence of coefficient of variation in determining significant difference of quantitative values obtained from
Katsumi Kobayashi1, Yuki Sakuratani, Takemaru Abe
1Chemical Management Center, National Institute of Technology and Evaluation (NITE), Tokyo, Japan. kobayashi-katsumi@nite.go.jp
Abstract:
In order to understand the influence of coefficient of variation (CV) in determining significant difference of quantitative values of 28-day repeated-dose toxicity studies, we examined 59 parameters of 153 studies conducted in accordance with Chemical Substance Control Law in 12 test facilities. Sex difference was observed in 12 parameters and 10 parameters showed large CV in females. The minimum CV was 0.74% for sodium. CV of electrolytes was comparatively small, whereas enzymes had large CV. Large differences in CV were observed for major parameters among 7-8 test facilities. The changes in CV were grossly classified into 11. Our study revealed that a statistical significant difference is usually detected if there is a difference of 7% in mean values between the groups and the groups have a CV of about 7%. A parameter with a CV as high as 30% may be significantly different, if the difference of the mean between the groups is 30%. It would be ideal to use median value to assess the treatment-related effect, rather than mean, when the CV is very high. We recommend using CV of the body weight as a standard to judge the adverse effect level.
Related Concept Videos
Coefficient of Variation
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
Bioequivalence Data: Statistical Interpretation
Toxicity Testing in Animals
Bioavailability Study Design: Single Versus Multiple Dose Studies
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...

