Search Results

10 results for “distribution”

Formulae (10)

f(x) = \frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{(x-\mu)^2}{2\sigma^2}}

Probability density of the bell curve.

P(X=k) = \binom{n}{k}p^k(1-p)^{n-k}

Probability of k successes in n trials.

P(X=k) = \frac{\lambda^k e^{-\lambda}}{k!}

Probability of k events in a fixed interval.

P(X=k) = \binom{n}{k} p^k (1-p)^{n-k}

Probability of k successes in n independent trials.

P(X=k) = \frac{\lambda^k e^{-\lambda}}{k!}

Probability of k events in a fixed interval given average rate λ.

P(X=k) = (1-p)^{k-1} p

Probability that the first success occurs on trial k.

f(x) = \frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{(x-\mu)^2}{2\sigma^2}}

Bell-curve probability density function.

\sigma(z_i) = \frac{e^{z_i}}{\sum_{j=1}^{K} e^{z_j}}

Converts a vector of scores into a probability distribution.

H = -\sum_{i=1}^{n} p_i \log_2 p_i

Measures the uncertainty or information content of a distribution.

WHR = \frac{\text{waist}}{\text{hip}}

Fat-distribution health indicator.