Random Sample Generator

Paste one item per line, choose a sample size, and draw a local random sample without duplicate positions.

Population — one item per line

Sample size

Random/decision tools run locally. Secure tools use browser Web Crypto randomness and rejection sampling; the seeded generator is deliberately deterministic and is labeled separately.

Core random, wheel & group workflows

Use the broad picker, number, wheel, name, team or dice workflow first. Move to a specialist only when the probability model or output structure genuinely changes.

All 35 random tools

Random Number GeneratorSecure integer draws & unique mode Random PickerPick names or items from a list Spin the WheelVisual choice wheel & winner history Random Name GeneratorGenerate names in local batches Random Team GeneratorSplit a roster into teams Dice RollerCustom dice count & sides Yes or No WheelBinary decision with visible odds Weighted WheelCustom non-negative probability weights

Fairness and randomness boundaries

Random selection can make equal-probability choices from the entered pool, but it cannot prove that the input list itself is appropriate or unbiased. Visual wheel/dice animations are presentation only. Seeded tools remain reproducible pseudo-random workflows rather than cryptographic randomness, and rating-balanced teams use a transparent heuristic rather than an optimal or human-judgment model.

Sample rows are positions, not deduplicated values

Sampling is without replacement across entered rows. If the same visible value appears twice, both rows can appear in the sample because they are distinct positions.

Practical guide and verification

Use the tool first, then apply these checks to verify the inputs, interpret the result, and hand it off without displacing the primary workflow.

Define the sampling frame before drawing

The generator can only sample the rows you provide. Missing, duplicated, filtered, or stale rows change the population before randomness begins. Confirm that every eligible unit appears with the intended multiplicity and that exclusions were decided before the draw.

Distinguish sampling rows from unique values

Two identical text rows can represent two separate eligible units or an accidental duplicate. The tool samples positions, not semantic identities. Deduplicate only when the underlying sampling design says repeated values should represent one unit.

Choose sample size before seeing the result

Changing the requested size after inspecting a draw can bias an informal selection process. Decide the target n and any replacement or stratification rules first. For statistical inference, sample-size adequacy depends on the analysis goal and cannot be guaranteed by a random picker alone.

Record the final sample and the source frame

For a reproducible handoff, keep the sampled rows together with the source list version, draw time, and any eligibility rules. The browser output proves the selected rows, but it cannot prove that the original frame was complete or unbiased.