SearchOnMath

Bayes's theorem, \(P(A|B) = \frac{P(B|A)P(A)}{P(B)}\), relates the two conditional probabilities involving events \(A\) and \(B\).

The natural logarithm can be expanded into a series, yielding \(\ln(1+x) = \sum_{k=1}^{\infty} \frac{(-1)^{k+1}x^k}{k}\).

Complicated convolution operations become simple multiplications via the Laplace transform \(F(s) = \int_{-\infty}^{\infty}f(x)e^{-s x}dx\) for function \(f\).