Base Rates & Conditional Rates
Always ask 'out of which group?' before you divide.
In your head, jot if needed · no calculator why?
Opens at level 37.
the lesson
Read the lesson
The idea
Every rate is a count divided by a group, and the group decides the answer. Before you divide, ask "out of which group?"
"The conversion rate among referrals" divides by referrals. "The share of buyers who were referrals" divides by buyers. Same counts, different questions, different answers.
The biggest trap is a warning sign for something rare. If 2% of orders are fraud, many flags can land on honest orders, because there are so many honest ones to be wrong about.
Techniques
Name the group, then divide
- Find the group after "among" or "of all". It goes on the bottom.
- On top, count only members of that group with the outcome.
- Say it back in words before you divide.
worked example
Referrals: 30 buy, 20 don't. Non-referrals: 10 buy, 40 don't. What share of all buyers were referrals?
- The group is buyers: 30 + 10 = 40.
- 30 ÷ 40 = 0.75 = 75%.
- A different question: among referrals, 30 ÷ 50 = 60% buy.
Answer: 75%
Turn rates into counts
- Split the population into the rare group and the rest.
- Apply each flag rate to its own group.
- Real share of flags: flagged rare ÷ all flagged.
worked example
Of 1,000 orders, 20 are fraudulent. A filter flags 90% of fraudulent orders and 5% of honest orders. If an order is flagged, what is the chance it's fraudulent? Round to the nearest whole percent.
- Flagged fraud: 90% of 20 = 18.
- Flagged honest: 5% of 980 = 49.
- 18 ÷ 67 ≈ 26.9%, about 27%.
Answer: 27%
Tips by skill
- TipRate within a group: Divide by the group after "among", not by everyone. On top go the ones in that group with the outcome.
- TipShare of buyers from a group: The group is now buyers: this group's buyers ÷ all buyers.
- TipFlagged: how likely is it real?: Turn the rates into counts, flagged fraud and flagged honest. Divide flagged fraud by all flagged orders.
- TipWhich denominator?: The whole group named after "among" goes on the bottom. Only those with the outcome go on top.
Watch out for
- Dividing by everyone instead of the group named. "Among referrals" means divide by referrals, not all leads.
- Answering the rate within a group when the question asks for a share of buyers, or the other way round.
- Confusing "flagged, given fraud" with "fraud, given flagged". A filter that catches 90% of fraud can still be wrong about most of its flags.
skills · practice stats
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Rate within a group not tried yet
worked example
There are 260 leads. 40 are referrals, and 7 of the referral leads buy. What is the conversion rate among referrals?
Answer: 17.5%
- "Among referrals" means divide by referrals: 7 ÷ 40 = 17.5%.
- Dividing by all 260 leads would answer a different question.
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Share of buyers from a group not tried yet
worked example
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Flagged: how likely is it real? not tried yet
worked example
Of 10,000 orders, 200 are fraudulent. A filter flags 90% of fraudulent orders and 2% of honest orders. If an order is flagged, what is the chance it's fraudulent? Round to the nearest whole percent.
Answer: 48%
- Flagged fraud = 90% of 200 = 180; flagged honest = 2% of 9,800 = 196.
- Among the 376 flagged orders: 180 ÷ 376 ≈ 47.9%, about 48%. When the bad group is small, false alarms pile up.
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Which denominator? not tried yet
worked example
You want the no-show rate among online bookings. What goes in the denominator?
- All bookings
- All online bookings
- All no-shows
- Online bookings that were no-shows
Answer: All online bookings
- The group after "among" is the whole you divide by: all online bookings.
- Only the ones that were no-shows go on top.
rest ladder
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