4 statistical processes that every data scientist should know

The depth and variety of skills that fit under the analytics umbrella are extensive. Different roles -- such as strategic analysts, digital analysts, data scientists, data engineers -- require distinct skillsets and varying levels of technical expertise. However, a handful of statistical processes are so common that every analyst should be acquainted with them. Further, it's beneficial to know how to code these in at least one programming language (or if not, in Excel). Below, are 4 of the most common and versatile statistical methods used in business, along with examples and educational sources.