ABSTRACT
This chapter discusses data sets subject to random error and how these values are normally distributed when built into a histogram chart. A z-score identifies a point on the horizontal axis of the distribution to identify how much data should occur within the z-score. Alternatively, a z-score also describes the probability of data within the distribution. For data that appear well outside the bounds of the rest of the data set, Chauvenet’s criterion can be used to assess whether data should exist at that particular point based on a 50% chance criterion.
