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🚌 The Inspection Paradox

Why Your Bus Is Always Late (And Your Friends Are More Popular)

🚏 The Bus Stop Simulation

Buses arrive every 10 minutes on average, but with random variation. You'd expect to wait 5 minutes on average... right?

🧍
5.0
Expected Wait (min)
If intervals were regular
-
Your Actual Avg Wait (min)
0
Times You've Arrived

📊 Why Longer Gaps Catch You

Here are the intervals between bus arrivals. Notice how you're more likely to land in the longer gaps!

Short interval
Long interval
Your arrival

💡 The Key Insight

If one gap is 30 minutes and another is 10 minutes, you're 3× more likely to arrive during the long gap!

You oversample long intervals simply because they occupy more time.

🎓 The Class Size Paradox

Same paradox, different context: Ask students their class size vs. ask the registrar.

👨‍🎓 Survey Students

Each student reports their class size

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Average reported

🏫 Ask the Registrar

Average class size from records

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Actual average
Students in large classes are oversampled — 100 students in a big class = 100 reports of "large", but only 10 students in a small class = 10 reports of "small"!

🧠 Understanding Size-Biased Sampling

The inspection paradox arises whenever the probability of observing something is related to its size. You don't sample uniformly — you sample proportionally to size!

The Mathematics:

For bus arrivals with mean interval T:

E[Wait] = E[T²] / (2 × E[T])

For exponential (Poisson) arrivals:

E[Wait] = T (not T/2!)

With regular 10-minute intervals, you'd wait 5 minutes on average.
With random Poisson arrivals (same 10-min average), you wait 10 minutes!

🌍 Where Else Does This Appear?

Hospital stays: Surveying patients oversamples long stays

Website visits: Active users are oversampled in traffic data

Checkout lines: You're more likely to join a slow line (more people in it)

Partner history: Your partners have had more partners than you (on average)

Epidemic tracking: Friends of random people get sick earlier (used for early warning!)