In this chapter we have discussed continuous probability distributions. We began by learning that a continuous probability distribution is described by a continuous probability curve and that in this context probabilities are areas under the probability curve. We next studied several important continuous probability distributions—the uniform distribution, the normal distribution, and the exponential distribution. In particular, we concentrated on the normal distribution, which is the most important continuous probability distribution. We learned about the properties of the normal curve, and we saw how to use a normal table to find various areas under a normal curve. We also saw that the normal curve can be employed to approximate binomial probabilities, and we demonstrated how we can use a normal curve probability to make a statistical inference. We concluded this chapter with an optional section that covers the cumulative normal table.