Lognormalise

Lognormalise is a term that can refer to a few related concepts, primarily concerning data transformation and distribution. In the context of data analysis, "lognormalise" often describes the process of transforming data that is believed to follow a log-normal distribution. A log-normal distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. This transformation is typically achieved by taking the natural logarithm of each data point. The purpose of this transformation is to convert skewed data into a more symmetrical, bell-shaped (normal) distribution, which can be advantageous for statistical methods that assume normality, such as linear regression or ANOVA.

Alternatively, "lognormalise" might also be used informally to describe the act of making a dataset or a set of values approximately log-normally distributed through various data manipulation techniques, not exclusively limited to a simple logarithmic transformation. The goal remains to improve the suitability of the data for statistical analysis or modeling. Understanding the underlying distribution of data is crucial before applying such transformations, as inappropriate log-normalization can distort the data's true characteristics.