Data Wrangling in Statistics and Visualization

A good data wrangling professional is expected to encounter a dizzying array of diverse data sources each day. As we explained previously, due to a multitude of complex sub-processes and mutual interactions that give rise to such data, they all fall into the category of discrete or continuous random variables.

It would be extremely difficult and confusing for a data wrangler or a data science team if all of this data continued to be treated as completely random without any shape or pattern. A formal statistical basis must be given to such random data streams, and one of the simplest ways to start that process is to measure their descriptive statistics.

Assigning a stream of data to a particular distribution function (or a combination of many distributions) is actually part of inferential statistics. However, inferential statistics starts only when descriptive statistics is done alongside measuring all the important parameters of...