Computer Methods for Sampling from the Exponential and Normal Distributions Various methods are known for transforming uniformly distributed random numbers into exponentially and normally distributed quantities. The most efficient ones are compared, in terms of memory requirements and speed, with some new algorithms. A number of procedures convert Taylor series expansions directly into sampling steps, an approach which may be used for sampling from any continuous distribution. For the exponential distribution a definite recommendation can be made, whereas in the case of the normal distribution there remains a choice between slower and shorter algorithms and faster but space consuming methods. CACM October, 1972 Ahrens, J. H. Dieter, U. random numbers, pseudorandom, normal distribution, exponential distribution, exponential distribution, simulation, numerical analysis 3.29 3.57 5.11 5.5 CA721002 JB January 27, 1978 3:55 PM 1073 4 2276 2137 4 2276 2276 4 2276 2276 4 2276 1073 5 2276 1153 5 2276 2276 5 2276 2276 5 2276 2276 5 2276 2565 5 2276 1716 6 2276 2276 6 2276