What You Will Be Able to Do
By the end of this lesson, you should be able to:
- Map a random generator's range into equal blocks for
choices - Detect the bias when the count doesn't divide the range evenly
- Fix it with a divisible range or rejection sampling, verifying each is
From Dice to a 1-to-100 Generator
A die has 6 equally likely faces. A generator gives equally likely integers — say 1 to 100.
Same idea: map them into equal blocks.
For k Choices, Generate 1 to k
The cleanest approach: generate an integer from 1 to k directly.
Each value is equally likely, so each choice gets
Map a Larger Range Into Equal Blocks
For 2 choices on a 1-100 generator: 1-50 and 51-100, each
A Fair Generator, an Unfair Mapping
The generator can be perfectly fair while the mapping is biased.
Two separate questions: is the generator fair? Are the blocks equal?
Predict: Is This Split Fair?
A 1-100 generator, 3 choices, split 1-33 / 34-66 / 67-100.
Is each choice equally likely? Commit before advancing.
Count the Blocks: 33 / 33 / 34
The third choice gets
Why: 100 Is Not Divisible by 3
That leftover 1 has to go somewhere — and wherever it goes gets favored.
Fix 1: Use a Divisible Range
Generate 1 to 99 instead of 1 to 100.
Now split into 1-33 / 34-66 / 67-99 — each exactly
Fix 2: Reject and Redraw (Rejection Sampling)
Keep 1-100, but reject 100 and redraw. Use only 1-99, split evenly.
Generalize: Reject the Top (n mod k)
To choose among k options with n equally likely outcomes:
Reject the top
Verify Each Choice Is Exactly 1/k
A procedure is fair only if you can show each choice's probability is
After any fix, count the block and confirm the fraction.
Resolve the Teaser: 5 With a Die
Five choices, a 6-sided die.
Use faces 1-5 for the five choices; re-roll on 6.
Your Turn: Find and Fix the Bias
A 1-1000 generator picks among 7 prizes, split into blocks of about 143.
Is it fair? If not, fix it and verify each is
What You Learned This Lesson
✓ Map a range into equal blocks — generate 1 to k when you can
✓ A leftover remainder biases one choice
✓ Reject the leftovers, redraw, and verify
Where Fair Randomness Goes Next
Fair random assignment underlies randomized sampling and experiments (HSS.IC).
And rejection sampling is how computers generate unbiased random integers.
Click to begin the narrated lesson
Use probabilities to make fair decisions