Multivariate data analysis of multivariate populations

For data that can be arranged in populations, multivariate data analysis of digitalized distributions is suggested as an alternative method to detect variations. This approach includes a representation of the data that avoids information destroying pre-processing such as averaging. The method is exemplified and discussed for both single variable distributions and multivariable distributions. A theoretical discussion is presented on its use with data from fibre measuring systems, time series and image analysis data. The method is suggested as either a complement or alternative to other types of data analysis and opens new possibilities for variation detection.