Generate single/multiple random integers or decimals with custom range, adjustable precision, and visual distribution histogram.
Generate one random integer within custom lower and upper integer limits, support large whole numbers.
Generate multiple random numbers, support integer or decimal mode with configurable decimal precision up to 999 digits.
| Control Item | Definition & Function | Input Example |
|---|---|---|
| Lower Limit Input | The minimum boundary value of random number range; can be integer or decimal | 1, -5, 0.2, -12.75 |
| Upper Limit Input | The maximum boundary value of random number range; must be larger than lower limit | 100, 2000, 112.5 |
| Numbers to Generate | Define how many random values will output in one calculation, positive integer only | 1, 10, 50 |
| Integer Radio Mode | Only output whole numbers, ignore decimal precision setting | Range 1~10 → 7 |
| Decimal Radio Mode | Output floating-point values with user-specified decimal digit precision | Range 0~1, precision 3 → 0.421 |
| Precision Digits Input | Control how many digits reserved after decimal point, range 1 ~ 999 | 10, 50, 200 |
| Green Generate Button | Read all input parameters, validate range rules, calculate random values, render result & histogram | Click after filling all limits |
| Grey Clear Button | Empty all input boxes of current module, hide its result panel and histogram canvas | Reset current module |
A random number is a value selected from a defined set of numbers with no predictable repeating pattern. Each generated value is statistically independent of previous results. Most random generators implement uniform distribution: all values within the specified range have equal probability of being selected. Real-world datasets such as human height often follow normal distribution, but this tool uses uniform flat distribution for general-purpose randomization.
Algorithm-based sequence generator seeded by system timestamp. Output sequences appear statistically random for daily use cases, but are fully deterministic if seed value is known. Not suitable for cryptography, encryption, or security-sensitive lottery applications.
Hardware-based generator extracting entropy from physical chaotic phenomena: atmospheric noise, thermal circuit noise, radioactive decay, quantum particle behavior. Requires hardware sensors and entropy bias compensation, used for cryptography and secure lottery systems.