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Mathematics · unit version 1

Probability protocols and expected work

Build the observation event, distinguish fresh restarts from retained information, and compare exact expected inspection work under explicit sampling assumptions.

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Readiness and preparation

Check your starting point

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Does observing a marked token mean the hand was sampled uniformly among hands containing a marked token?

The reporting mechanism determines the conditional distribution.

Compare reasoning and find a refresher

Not generally. Randomly revealing a hand member weights a hand by its fraction of marked tokens. Conditioning on containment instead weights every qualifying hand equally.

Review conditioning and independence

Does adding expected costs require independent costs?

Inspection-tree tests can be dependent even when item defects are independent.

Compare reasoning and find a refresher

No. Linearity applies to finite sums with finite expectations. Independence is used separately when deriving a pool’s negative probability.

Review discrete distributions and waiting times

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Audit the observation rule and expected workload

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Lesson sequence

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  1. Condition on the observation protocol, not just its words

    Lesson details and objectives

    Count hands and reveal outcomes separately, derive size-weighted posteriors, and track how a reporting policy changes the evidence.

    • Distinguish containment information from uniformly revealing a hand member through complete finite sample spaces.
    • Derive the hypergeometric marked-count law and its reveal-weighted posterior with explicit ranges and positive conditioning.
    • Prove the particular-token residual-hand formula and diagnose changed reporting policies and boundary cases.

    6 practice tasks.

  2. Analyze restarted experiments and their actual work

    Lesson details and objectives

    Separate terminal outcome probabilities, unresolved capped runs and expected attempts, while checking that a restart really reproduces the same independent experiment.

    • Derive eventual success and almost-sure termination from disjoint finite stopping events.
    • Compute capped probabilities and expected work by finite geometric sums before taking limits.
    • Handle certain restart and diagnose when retained state invalidates an iid restart equation.

    6 practice tasks.

  3. Compare expected work in pooled factory inspection

    Lesson details and objectives

    Derive inspection costs from an explicit branching protocol, bound a rare-defect approximation, and change the sampling and recursion assumptions.

    • Derive exact expected inspections per pool and per item under independent defects and compare feasible equal-pool plans.
    • Prove a controlled approximation and distinguish its continuous optimizer from an exact integer decision.
    • Analyze fixed-defect populations and a specified binary inspection tree using indicators rather than unsupported independence.

    6 practice tasks.