Way back in the 18th century, a French scholar and polymath by the name of Pierre-Simon Laplace developed a formula to compute probabilities starting from low observation counts. Assume there have been n independent trials that can only result in success or failure; we might then compute the probability (p) of success (s) on the next trial (n) by applying the following formula: p = s / n. However, let’s say there have been just five independent trials and five successes. The probability of success on the sixth trial would therefore equal 100%; alternatively, if there had instead been five failures, the probability of success would equal 0%. The traditional or customary way of computing probabilities doesn’t make an allowance for a different outcome where and when the observation count is low and the opportunity for variance is relatively minimal, and therefore not terribly meaningful.