# Probable-Certainty By:: [[Ross Jackson]] 2022-09-25 Analytics makes pronounced use of statistics. As such, analytics is a discipline of applied probability. In this area, certainty frequently seems to recede into the background. To the degree to which business [[rhetoric]] conveys certainty, there is a disconnect between the language of analysis and the one desired by commerce. When forced for a definitive stance, analysts tend to demur. But the language used in analytics reveals something interesting upon closer scrutiny. The divide between the probable and the certain can even be observed within the language of analytics itself. An analyst can discuss statistical results in terms of contingencies but discuss one’s assessments in terms of certainty. A statement along the lines, “The results show a 20% chance of [[success]],” provides an example of the epistemological tension within analytics. The portion of the statement, “the results show,” is a declarative certainty, whereas “a 20% chance of success” is probabilistic. Analytics operates across the probable-certainty spectrum. Analysts, especially those narrowly focused on applied mathematics, sometimes explain that they aren’t good with language and writing. This is problematic as analysts navigate probable-certainty. Language shapes, constrains, and reflects thinking. If one is unable to communicate these nuances, it is unclear the degree to which one understands them. This can produce at least three different negative outcomes. First, an analyst might overstate the certainty of one’s results. Second, an analyst might be overly contingent on one’s assertions with management. Third, an analyst might present an inconsistent mess of muddled epistemology. Each of these three results is counterproductive to integrating analysis effectively in organizations. #### Related Items [[Analytics]] [[Statistics]] [[Probability]] [[Communication]] [[Language]] [[Business]]