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SCIENCE · INVESTIGATE AND EXPLAIN

Predeclare review triggers across repeated observations

A monitoring plan should specify what observation triggers review, what confirms the signal and who is authorized to revise action. Looking repeatedly for an unusual result creates more opportunities for a false alarm. That statistical issue is distinct from the ecological consequences of missing a true problem.

Learning outcome: Compare one,six and twelve looks at 0.05. Explain the independence limitation, then write a review/confirmation/escalation rule without presenting this toy alpha as a regulatory threshold.

Starting recap

Preserve packet identity, independent units, analysis recipe, outcome constraints and review authority; distinguish scientific uncertainty from stakeholder value choices.

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Try

At per-look 0.05 and six independent looks, at-least-one false alarm is 1−0.95⁶≈0.26491. The dependence-agnostic union bound is 0.30. For a total target 0.05, Bonferroni per-look level is 0.05/6≈0.008333.

Open the experiment

Predict

Bonferroni family control fundamentally uses:

Experiment

Compare one,six and twelve looks at 0.05. Explain the independence limitation, then write a review/confirmation/escalation rule without presenting this toy alpha as a regulatory threshold.

Predeclare repeated-look error accounting

Worked teaching model · synthetic values · All no-change nulls true. Independent looks give at-least-one false alarm 1−(1−α)^m. Without independence, union bound≤min(1,mα). To allocate a total family target equal to the chosenα, Bonferroni per-look levelα/m. No actual regulatory trigger or assumption that serial environmental observations are independent.

Reset keeps your prediction, captures and practice history.

Original synthetic system; units differ by row
QuantityValueUnit
False-alarm probability per look0.05fraction
Planned looks6looks
Independent-look at-least-one false alarm0.2649081fraction
Union-bound upper limit without independence0.3fraction
Bonferroni per-look level for total target alpha0.008333333fraction

Repeated unadjusted opportunities to trigger increase the chance of at least one false alarm.

Environmental time series are often correlated, so the independence expression is a scenario, not an automatic field estimate. Predeclare review thresholds, confirmation evidence and safety/escalation responsibilities; statistical alarm control does not replace ecological consequence assessment.

Predict, change one control, and retain contrasting captures. Reconstruct the analysis and decision rule before opening feedback. Display precision is not measurement precision.

Repeated unadjusted opportunities to trigger increase the chance of at least one false alarm.

Environmental time series are often correlated, so the independence expression is a scenario, not an automatic field estimate. Predeclare review thresholds, confirmation evidence and safety/escalation responsibilities; statistical alarm control does not replace ecological consequence assessment.

Captures preserve recipes and replay their calculated results. They are synthetic model evidence, not physical measurements.

Understand

Define the decision and evidence boundary

A monitoring plan should specify what observation triggers review, what confirms the signal and who is authorized to revise action. Looking repeatedly for an unusual result creates more opportunities for a false alarm. That statistical issue is distinct from the ecological consequences of missing a true problem.

Reconstruct the transparent method

If m looks are independent and each has false-alarm probability α when no change exists, the probability of at least one alarm is 1−(1−α)^m. Without independence, the union bound gives an upper limit min(1,mα). Environmental records are often serially correlated, so independence must not be assumed merely because measurements have different dates.

Interpret the comparison

For a total family target α across m predeclared looks, a Bonferroni allocation uses per-look levelα/m. The bound does not require independence, but may be conservative. A more elaborate sequential procedure needs its own justified design; repeatedly resetting the monitoring family after an inconvenient result changes the original error accounting.

Predeclare limitations and revision

A review trigger is not automatic permission for a physical intervention. A responsible plan retains raw data, verifies measurement quality, assesses effect size and ecological relevance, checks safety/legal constraints and records the authorized decision. Urgent safety signals may require separate escalation rules rather than waiting for a statistical threshold.

Worked original packet

At per-look 0.05 and six independent looks, at-least-one false alarm is 1−0.95⁶≈0.26491. The dependence-agnostic union bound is 0.30. For a total target 0.05, Bonferroni per-look level is 0.05/6≈0.008333.

Investigation

Compare one,six and twelve looks at 0.05. Explain the independence limitation, then write a review/confirmation/escalation rule without presenting this toy alpha as a regulatory threshold.

Changed-case transfer

At per-look 0.02 and ten looks, calculate independent family probability, union bound and per-look level for total target 0.02.

Feedback

Independent probability 1−0.98¹⁰≈0.182927; union bound 0.20. Bonferroni level 0.002 gives a family upper bound 0.02 under valid per-look tests; it does not establish power or practical importance.

Sources and evidence boundary

Original prose, dataset and numerical exercises. Primary method/mechanism source, checked 30 October 2026. The versioned packet is synthetic, not observed fieldwork. No treatment implementation, site access, pollutant handling or real management authorization is requested. Preserve first reasoning and critique in the course workspace.

Apply

Bonferroni family control fundamentally uses:

Public practice checks a specific claim. It does not establish independent mastery.

At per-look 0.02 and ten looks, calculate independent family probability, union bound and per-look level for total target 0.02.

Continue

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