I recently ran across the fact that
is a remarkably good approximation for −1 ≤ x ≤ 1.
Since the integral above defines the error function erf(x), modulo a constant, this says we have a good approximation for the error function
again provided −1 ≤ x ≤ 1.
The error function is closely related to the Gaussian integral, i.e. the normal probability distribution CDF Φ. The relation between erf and Φ is simple but error-prone. I wrote up some a page notes for myself a few years ago so I wouldn’t make a mistake again moving between these functions and their inverses.
You can derive the approximation by writing out the power series for exp(t), substituting −t² for t, and integrating term-by-term from 0 to x. You’ll see that the result is the same as the power series for sine until you get to the x5 term, so the error is on the order of x5. Here’s a plot of the error.
The error is extremely small near 0, which is what you’d expect since the error is on the order of x5.