Overview
Sampling unique random integers without replacement from a discrete pool is the mathematical foundation of lotteries, raffle ticket selection, contest prize giveaways, and randomized cohort trials. The Random Integer Generator draws a specified subset of unique integers from any integer pool [Min, Max], sorting and presenting results instantly.
Unlike general random number tools that permit duplicate numbers, this specialized integer generator enforces strict uniqueness (sampling without replacement). It also computes the total theoretical combinations C(n, k) according to combinatorial probability theory.
Worked Examples
Example 1: Classic 6/49 Lottery Draw (Seed = 123)
Min = 1, Max = 49, Pick Count = 6, Sort = Ascending, Seed = 123
- Pool size n = 49 − 1 + 1 = 49 numbers.
- Total combinations: C(49, 6) = 13,983,816 possible tickets.
- Draw 6 unique integers using deterministic PRNG.
- Sort numbers in ascending order.
Final Answer: 7, 14, 21, 33, 40, 48 (Sum: 163 | C(49,6) = 13,983,816)
Example 2: Raffle Drawing 3 Winners from 100 Tickets (Seed = 88)
Min = 1, Max = 100, Count = 3, Sort = Ascending, Seed = 88
- Pool size n = 100, Pick k = 3.
- Combinations: C(100, 3) = (100 × 99 × 98) / 6 = 161,700.
- Draw 3 unique ticket numbers.
Final Answer: 23, 67, 92 (All unique winners)
Example 3: Coin Flip Simulator (1 = Heads, 2 = Tails)
Min = 1, Max = 2, Count = 1, Seed = 50
- Binary choice between 1 and 2.
- Draw single integer.
Final Answer: 2 (Tails)