Intro to Biostatistics
The Box-Cox transformation is a family of power transformations designed to stabilize variance and make the data more closely resemble a normal distribution. This transformation is particularly useful when data do not meet the assumptions of normality or homoscedasticity, which are crucial for many statistical analyses. By applying the Box-Cox transformation, researchers can improve the validity of their results and ensure that the underlying assumptions of statistical tests are satisfied.
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