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Statistical murder

Statistical murder is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Statistical murder rather than just read about it. In short: When a business or regulator uses limited funds to take an action that saves a limited number of lives, instead of an alternative action that would save more lives, this decision is sometimes called statistical murder. This phrase is currently primarily a term of political advocacy, used to draw attention to unwise decision making that either is not the most effective available or is potentially even harmful.

Key takeaways

  • Statistical murder belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Statistical murder to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Statistical murder from memory before moving on to harder problems.

Reference excerpt

When a business or regulator uses limited funds to take an action that saves a limited number of lives, instead of an alternative action that would save more lives, this decision is sometimes called statistical murder. This phrase is currently primarily a term of political advocacy, used to draw attention to unwise decision making that either is not the most effective available or is potentially even harmful. This phrase is a diffuse neologism. The phrase originated in the early 1990s with Professor John D. Graham, a tenured professor of policy and decision sciences at Harvard University's school of Public Health and director of the Harvard Center for Risk Analysis.[1] This phrase appears in the Congressional Record in February, 1995 where he is quoted thus "John Graham, a Harvard professor, who said, 'Sound science means saving the most lives and achieving the most ecological protection with our scarce budgets. Without sound science, we are engaging in a form of "statistical murder," where we squander our resources on phantom risks when our families continue to be endangered by real risks." In 2001 he was appointed the head of the U.S. Office of Information and Regulatory Affairs in the Office of Management and Budget by George W. Bush, making him the top regulator for the United States. Because the analysis underlying the term was controversial among those interested in U.S. government policy, the senate confirmation process for nomination made the term more widely known. To show that something is statistical murder requires that a comparative risk analysis be done on the available alternatives. This is akin to a cost-benefit analysis but does not entail the translation of lives and health into dollars. However, if other types of benefits are to also be evaluated, the comparative risk analysis approach may not viable, so a cost-benefit analysis must be done. Additionally, the concept implies that the inefficiently spent resources could in fact be transferred to a more effective alternative. This requires that regulators and policy makers with budgetary authority at least allow such transfers and preferably use cost-benefit analysis to plan the budgeting. This was not the practice at the time the phrase was coined, and has not yet become standard practice in the U.S.

Criticism of concept Some people object to the required analysis because they believe it is always wrong to put a financial value on human life. They would have no objection to a risk assessment because it only measures lives lost. However, with this limitation it also cannot value any effects other than the number of human lives lost - including non-fatal human diseases, effects on non-human species, and effects on human activities and enjoyment. It is quite possible to make errors in the statistics used to do the analysis, and in 2002 Richard Parker, a law professor at the University of Connecticut, argued that all the widely published studies suffered from unacceptable flaws. An alternative view, taken by some policy analysts, is that it is not sufficient to look solely at outcomes, but also at feelings. If a risk is perceived to be significant, but is in fact insignificant, it may nonetheless be appropriate to respond in some way to that risk. Proponents of this view suggest using an expected utility calculation instead.

References

Worked examples

Example 1 — a first encounter with Statistical murder

Start with the simplest possible case. Write down what Statistical murder claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Statistical murder before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Statistical murder ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Statistical murder

In research
Statistical murder appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Statistical murder in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Statistical murder is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1990s neologisms, Decision analysis, Political neologisms, so understanding it makes those chapters shorter.
In everyday life
Look for Statistical murder outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Statistical murder in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Statistical murder means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Statistical murder out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Statistical murder in simple terms?

When a business or regulator uses limited funds to take an action that saves a limited number of lives, instead of an alternative action that would save more lives, this decision is sometimes called statistical murder. This phrase is currently primarily a term of political advocacy, used to draw at…

Why does Statistical murder matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Statistical murder?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Statistical murder.

Tags

  • 1990s neologisms
  • Decision analysis
  • Political neologisms

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