Our Random Number Generator lets you quickly create unbiased integers or decimals within any range you choose. Whether you need a single number for a giveaway or a large set for simulations, testing, or sampling, this tool is flexible, fast, and simple to use.
What is a Random Number Generator?
A Random Number Generator (RNG) produces numbers that are unpredictable within a specified range. In practical terms, this means when you ask the tool for a number between a minimum and maximum, each valid value has a fair chance of being selected. RNGs are used across data science, research, education, gaming, and everyday tasks like picking winners, shuffling lists, or creating sample datasets.
How to Use This Random Number Generator
Start by entering a minimum and maximum value. Choose how many numbers you want, whether duplicates are acceptable, and optionally select how many decimal places to include. If you need to avoid specific values, add them to the exclusion list using commas. Finally, decide how you want the results sorted: not at all, ascending, or descending.
Step-by-step
- Enter your Minimum and Maximum values. The range is inclusive.
- Set the Quantity of numbers to generate.
- Choose Decimal places: use 0 for whole numbers, or set a precision for decimals.
- Tick Allow duplicates if repeated values are acceptable.
- Optionally add Exclusions (comma-separated) to skip specific values.
- Pick a Sort option: none, ascending, or descending.
- Click Generate to see your results instantly.
Why Use This RNG?
- Flexible: integers or decimals, with customizable precision.
- Control: exclude values, choose duplicates on/off, and sort results.
- Transparent: the range is inclusive and clearly reported with each run.
- Reproducible: optional seed input can help you reproduce the same sequence for testing or documentation.
Popular Use Cases
Random number generation underpins many common workflows. Educators create practice data and randomized quiz elements. Analysts simulate outcomes, perform Monte Carlo methods, or bootstrap statistics. QA teams randomize test inputs to reveal edge cases. Event organizers pick winners fairly and transparently. Even hobbyists use RNGs to pick lottery numbers, decide meals, or assign tasks.
Tips for Best Results
- Define a sensible range: ensure the minimum is less than or equal to the maximum. If you enter them reversed, the tool will handle it, but it’s clearer to set them correctly.
- Pick the right precision: use 0 decimal places for whole numbers, or increase precision for scientific or financial simulations.
- Use exclusions to prevent specific values (like outliers or identifiers) from appearing.
- Disable duplicates when you need a unique sample without repeats.
- Sorting is optional. Keep the original order for unbiased sequence analysis; sort when you need a tidy list.
Understanding Duplicates and Exclusions
When duplicates are allowed, the generator may repeat values, which is expected in many statistical processes. When duplicates are disabled, the tool ensures each output is unique. If you also provide exclusions, the generator will avoid those values entirely. If your requested quantity exceeds the number of unique values available after exclusions, the tool will alert you so you can adjust your inputs.
Precision and Decimals
The decimal places setting determines how your numbers are rounded and displayed. For instance, with 2 decimal places, results like 3.14159 become 3.14. This is useful for simulations requiring uniform resolution (e.g., tenths or hundredths) or when aligning with a measurement system.
Reproducibility with Seeds
If you need the same sequence again for testing or documentation, provide a seed. Seeding initializes the pseudo-random process so the same inputs produce the same outputs, improving reproducibility in analytics and QA workflows.
Get Started
Enter your range, choose your options, and click Generate. You’ll see a clear summary of your settings and the resulting list of random numbers, ready to copy or export into your workflow.