ABSTRACT
Continuous distributions are developed from random variables that take fractional or decimal values such that numbers run into each other. As illustrated in the Icebreaker, the nominal volume of beer in a can is indicated on the label as 33 cl. However, the actual volume may be 32.8785, 32.9856, or 33.0528 cl., that is a number close to, but not exactly, 33 cl. Similarly, the actual weight of the bar of chocolate may be 99.7285, 100.1285, or 100.2459 grams, or the length of the fabric may be 2,998; 3,002; or 3,105 mm. For all these values of volume, weight, and length there is no distinct cut-off point between data values and they can overlap into other class ranges. This is different from discrete data where the numbers 1, 2, 3, 4, : : : etc. might represent the number of employees, the number ofmanufactured products, or the number of hotel clients.Here there is a distinct separation of data values. There are many families of continuous distribution and those considered in this chapter are thenormal distribution and a variant of this, the asymmetrical distribution; exponential distribution; and the beta distribution.
The normal distribution
