Practical Predictive Analytics

Levels of measurement

Levels of measurement is a classification system for classifying data into 4 different categories which is discussed as follows (ratio, ordinal, interval, and nominal). It is an important aspect of the project or studies metadata.

Levels of measurement is important in the world of predictive analytics since the specific measurements will often dictate which algorithm or techniques can be applied. For example k-means clustering does work if you want to incorporate nominal data, and logistic regression can not use ratio data as a dependent variable (although you can transform variables to a lower scale).