True or False: Normalization is applicable only to quantitative data.

Normalization is a process typically used to adjust values in a dataset to a common scale, often for the purpose of making the data comparable. This process is primarily associated with quantitative data, as it involves mathematical transformations to achieve this comparability. For example, normalization can include techniques like min-max scaling or z-score normalization, which are applied to numerical values to tease out patterns or reduce bias in datasets.

While qualitative data can be transformed and categorized, it does not undergo normalization in the same mathematical sense because qualitative data is not inherently numerical. Therefore, normalization, as traditionally understood in the context of sustainability accounting and data analysis, is indeed applicable only to quantitative data.