Someone asked me this week for C++ code to compute the inverse of the normal (Gaussian) distribution function. The code I usually use isn’t convenient to give away because it’s part of a large library, so I wrote a stand-alone function using an approximation out of Abramowitz and Stegun (A&S). There are a couple things A&S takes for granted, so I decided to write up the code in the spirit of a literate program to explain the details. The code is compact and portable. It isn’t as fast as possible nor as accurate as possible, but it’s good enough for many purposes.