Random Number Generator

A random number generator selects values without following a predictable user-controlled pattern. This tool creates whole numbers or two-decimal values between an inclusive minimum and maximum. It is useful for classroom sampling, games, drawings, test data, simulations, randomized ordering, and any task that needs quick independent selections from a defined numeric interval. For whole numbers, every integer from the rounded-up minimum through the rounded-down maximum has an equal chance on each draw. Decimal mode samples a continuous position in the interval and rounds it to two decimal places for display. Because rounding maps many underlying values to each displayed decimal, edge values can have slightly different probabilities. Use specialist statistical software or a cryptographic protocol when exact distribution guarantees are required. Allowing duplicates means each draw is independent, so the same value may appear more than once. Disallowing duplicates keeps drawing until every displayed result is different. Unique integer generation is only possible when the requested quantity does not exceed the count of available integers. For example, the inclusive range 1 through 10 contains ten distinct whole numbers. Decimal mode has many possible displayed values, but a very narrow range can still limit uniqueness after rounding. Random outputs are not the same as truly unpredictable physical randomness. Browser software usually relies on a pseudorandom sequence produced by the runtime. It is adequate for ordinary games, informal sampling, demonstrations, and synthetic examples, but this calculator is not designed for passwords, encryption keys, regulated lotteries, or security-sensitive decisions. Those uses need a documented cryptographically secure source and often an auditable selection process. Set the bounds carefully before generating. Negative values are supported, and the minimum may equal the maximum when duplicates are allowed or only one unique value is requested. A larger quantity helps simulations approximate an expected distribution, but random variation never guarantees an even count in a small sample. Save or copy results before generating again because each click intentionally replaces the previous sequence. The generator caps a request at 1,000 values so the page remains responsive and the output stays practical to inspect.