A/B Tests
Compare two versions fairly, read the result honestly, and ask if it's worth it.
Pen and paper is fine · no calculator needed why?
Opens at level 41.
Lesson and untimed practice
Read the full lesson and try each skill without a clock. About 3 minutes to read.
skills · practice stats
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Difference in points not tried yet
worked example
Variant A converts 48 of 200 recipients; B converts 350 of 1,000. What is the difference in percentage points (B minus A)? (Use a minus sign if negative.)
Answer: 11 points
- A = 48 ÷ 200 = 24%; B = 350 ÷ 1,000 = 35%.
- The difference is 11 percentage points. On its own this doesn't prove the difference is real.
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Relative lift not tried yet
worked example
A gets 4 purchases from 100 recipients; B gets 5 from 100. What is B's relative lift over A?
Answer: 25%
- Rates: A = 4%, B = 5%.
- (B − A) ÷ A = 1 ÷ 4 = 25%.
- That is a 25% relative lift; in absolute terms the rates differ by 1 percentage points.
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Read the interval not tried yet
worked example
An estimated conversion lift is 1.5 percentage points, with a 95% interval from −2.5 to 5.5 points. What can you conclude?
- B is proven better
- The effect is proven to be zero
- There's a 95% chance the lift is exactly 1.5 points
- It includes zero, so it doesn't rule out no effect
Answer: It includes zero, so it doesn't rule out no effect
- The interval runs from −2.5 to 5.5, so zero is inside it: "no effect" hasn't been ruled out, but it hasn't been proven either.
- An interval shows the range of effects the data are consistent with.
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Significant, but worth it? not tried yet
worked example
A statistically significant change adds $3,270 of expected contribution a month and costs $3,920 a month to run. What is its net monthly result? (Use a minus sign if negative.)
Answer: -$650.00
- $3,270 − $3,920 = −$650.
- "Significant" means the result would be unlikely if there were no real effect, not that the effect is big or worth paying for.
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Design a fair test not tried yet
worked example
You want to compare two pricing pages. Which plan is fair?
- Run A this week and B next week
- Randomly split comparable site visitors between A and B at the same time
- Give A to longtime customers and B to new prospects
- Show B only to people who responded last time
Answer: Randomly split comparable site visitors between A and B at the same time
- Random assignment at the same time makes the groups alike, so the only systematic difference is the thing you changed.
- Decide the sample size and the metric before you look.
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