numpy.random.choice(a, size=None, replace=True, p=None) Generates a random sample from a given 1-D array

numpy.random.ranf(size=None) Return random floats in the half-open interval [0.0, 1.0). Results are from the ?continuous

RandomState.standard_t(df, size=None) Draw samples from a standard Student?s t distribution with df

RandomState.vonmises(mu, kappa, size=None) Draw samples from a von Mises distribution. Samples are drawn

numpy.random.randn(d0, d1, ..., dn) Return a sample (or samples) from the ?standard normal? distribution. If positive

numpy.random.random(size=None) Return random floats in the half-open interval [0.0, 1.0). Results are from the

RandomState.normal(loc=0.0, scale=1.0, size=None) Draw random samples from a normal (Gaussian) distribution.

RandomState.noncentral_f(dfnum, dfden, nonc, size=None) Draw samples from the noncentral F distribution

RandomState.power(a, size=None) Draws samples in [0, 1] from a power distribution with positive exponent a - 1

numpy.random.multivariate_normal(mean, cov[, size]) Draw random samples from a multivariate normal distribution