Random Number Generator

Generates random numbers within a user-specified range using selectable distributions. Conceptually, a seeded PRNG produces a sequence of numbers that map to the desired domain. For uniform distribution, values fall evenly across [min, max); for normal distribution, values cluster around the mean with defined stddev. The tool is useful for testing, simulations, data sampling, and educational demonstrations. Users can specify a seed for reproducibility, choose distribution type, and control output size. Core value lies in the balance of simplicity, speed, and deterministic results when a seed is provided, plus the flexibility to switch distributions without scripting. Use cases include creating mock datasets, stress testing input handling, and validating statistical workflows. Core features include batch generation, numeric formatting, and easy export of results for analysis and reproducibility.