Create an rng object with np.random.default_rng(), you can seed it for reproducible results. You can draw samples from probability distributions, including from the binomial and normal distributions.

Use NumPy's RNG to make random arrays for quick testing of stats functions. Generate normal data and set mean/std by adding and scaling; visualize with Seaborn. Run regressions and correlations ...