Survey/sample distribution term. 'Bell curve' is the common informal term for a graph with a large rounded peak in the middle, sloping sharply to the right and left and then tapering more gently at the extreme ends of the graph. It's a bell-shape, hence the name. The term 'bell curve' refers also to this sort of statistical distribution, even if it is not actually graphed. Technically in probability theory, mathematics and marketing, etc., the 'bell curve' is 'normal' distribution or Gaussian distribution (after German mathematician ohann Carl Friedrich Gauss). The bell curve is very commonly exhibited in sampling and surveys, where the vast majority of results/subjects/data tend to concentrate towards the average score, with incidence of variation above and below the average (shown graphically right and left) being roughly equal to each other, and much less than the incidence/results towards the average and majority. Business people often refer to a 'bell curve' when anticipating/explaining a situation where the vast majority of members of an audience or market are very similar, and only a very small minority is outside of the 'norm' or average. This terminology is helpful in emphasizing the needs or tendencies of the big majority, and avoiding distraction by or over-estimating the effect of minority interests/needs, which can cause projects to be distorted unnecessarily. There is a broad correlation between the notion of a 'bell curve' and Pareto theory, also known as the '80-20 Rule', i.e., both concepts highlight the significance of concentration and distribution when assessing opportunity, risk, effectiveness, and the targeting of communications, resources, etc. (Separately note for interest, the contrast between 'bell curve' and 'bathtub curve' graphs and what they mean)