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 binomial theorem, making use of the well-known binomial coefficients, allows expressing \((x+y)^n\) as a sum: \((x+y)^n=\sum_{k=0}^{n} \binom{n}{k} x^k y^{n-k}\).

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