What Is a Bell Curve?
Remember the Bell Curve in school? The idea was that everyone’s grades were compared to the class’s average score. As long as nobody “blew the curve”, everyone came out ok-even when the class average was 54%! That bell curve, also called the “normal curve”, is a great tool for looking at group performance. Technically, that bell shape is created when results are truly random. More results occur around the average of the data and less occur at either extreme. This gathering of the data around the average is what causes the distinctive shape. When that bell shape changes, you have an issue. Statistically speaking, the bell curve is defined entirely by its mean (average) and its standard deviation. But for our purposes we need know only that its shape can tell us a lot about agent group performance.
A bell curve is a graph which depicts a normal distribution of variables, in which most values cluster around a mean, while outliers can be found above and below the mean. For example, human height often follows a bell curve, with outliers who are unusually short and tall and the bulk of people being concentrated around a mean height, such as 70 inches (178 centimeters) for American men. When data which follows a normal distribution pattern is graphed, the graph often resembles a bell in cross section, explaining the term “bell curve.” Normal or Gaussian distributions can be found in a wide variety of contexts, from graphs of the performance of financial markets to test scores. When variables are graphed and a bell curve appears, this is often taken to mean that the variables were within normal expectations, and that they are behaving in a predictable manner. If the graph is skewed or irregular, it can indicate that there is a problem. Ideally, a bell curve is symmetrical. In scoring,
