For linear regression to provide valid results, certain assumptions must be met. These include linearity, where the relationship between the variables is linear; independence, meaning the observations are independent of each other; homoscedasticity, where the residuals have constant variance; and normality, where the residuals are normally distributed. In toxicology, violating these assumptions can lead to inaccurate conclusions about the toxicity of substances.
