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Mean-preserving spread

Mean-preserving spread 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 Mean-preserving spread rather than just read about it. In short: In probability and statistics, a mean-preserving spread (MPS) is a change from one probability distribution A to another probability distribution B, where B is formed by spreading out one or more portions of A's probability density function or probability mass function while leaving the mean (the expected value) unchanged. As such, the concept of mean-preserving spreads provides a stochastic ordering of equal-mean g…

Key takeaways

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

Reference excerpt

In probability and statistics, a mean-preserving spread (MPS) is a change from one probability distribution A to another probability distribution B, where B is formed by spreading out one or more portions of A's probability density function or probability mass function while leaving the mean (the expected value) unchanged. As such, the concept of mean-preserving spreads provides a stochastic ordering of equal-mean gambles (probability distributions) according to their degree of risk; this ordering is partial, meaning that of two equal-mean gambles, it is not necessarily true that either is a mean-preserving spread of the other. Distribution A is said to be a mean-preserving contraction of B if B is a mean-preserving spread of A. Ranking gambles by mean-preserving spreads is a special case of ranking gambles by second-order stochastic dominance – namely, the special case of equal means: If B is a mean-preserving spread of A, then A is second-order stochastically dominant over B; and the converse holds if A and B have equal means. If B is a mean-preserving spread of A, then B has a higher variance than A and the expected values of A and B are identical; but the converse is not in general true, because the variance is a complete ordering while ordering by mean-preserving spreads is only partial.

Example This example shows that to have a mean-preserving spread does not require that all or most of the probability mass move away from the mean. Let A have equal probabilities 1 / 100 {\displaystyle 1/100} on each outcome x A i {\displaystyle x_{Ai}} , with x A i = 198 {\displaystyle x_{Ai}=198} for i = 1 , … , 50 {\displaystyle i=1,\dots ,50} and x A i = 202 {\displaystyle x_{Ai}=202} for i = 51 , … , 100 {\displaystyle i=51,\dots ,100} ; and let B have equal probabilities 1 / 100 {\displaystyle 1/100} on each outcome x B i {\displaystyle x_{Bi}} , with x B 1 = 100 {\displaystyle x_{B1}=100} , x B i = 200 {\displaystyle x_{Bi}=200} for i = 2 , … , 99 {\displaystyle i=2,\dots ,99} , and x B 100 = 300 {\displaystyle x_{B100}=300} . Here B has been constructed from A by moving one chunk of 1% probability from 198 to 100 and moving 49 probability chunks from 198 to 200, and then moving one probability chunk from 202 to 300 and moving 49 probability chunks from 202 to 200. This sequence of two mean-preserving spreads is itself a mean-preserving spread, despite the fact that 98% of the probability mass has moved to the mean (200).

Mathematical definitions Let x A {\displaystyle x_{A}} and x B {\displaystyle x_{B}} be the random variables associated with gambles A and B. Then B is a mean-preserving spread of A if and only if x B = d ( x A + z ) {\displaystyle x_{B}{\overset {d}{=}}(x_{A}+z)} for some random variable z {\displaystyle z} having E ( z ∣ x A ) = 0 {\displaystyle E(z\mid x_{A})=0} for all values of x A {\displaystyle x_{A}} . Here = d {\displaystyle {\overset {d}{=}}} means "is equal in distribution to" (that is, "has the same distribution as"). Mean-preserving spreads can also be defined in terms of the cumulative distribution functions F A {\displaystyle F_{A}} and F B {\displaystyle F_{B}} of A and B. If A and B have equal means, B is a mean-preserving spread of A if and only if the area under F A {\displaystyle F_{A}} from minus infinity to x {\displaystyle x} is less than or equal to that under F B {\displaystyle F_{B}} from minus infinity to x {\displaystyle x} for all real numbers x {\displaystyle x} , with strict inequality at some x {\displaystyle x} . Both of these mathematical definitions replicate those of second-order stochastic dominance for the case of equal means.

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Worked examples

Example 1 — a first encounter with Mean-preserving spread

Start with the simplest possible case. Write down what Mean-preserving spread 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 Mean-preserving spread 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 Mean-preserving spread 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 Mean-preserving spread

In research
Mean-preserving spread 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 Mean-preserving spread 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
Mean-preserving spread is common in secondary-school and first-year university syllabi. It links to neighbouring topics Decision theory, Theory of probability distributions, so understanding it makes those chapters shorter.
In everyday life
Look for Mean-preserving spread 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 Mean-preserving spread in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Mean-preserving spread 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 Mean-preserving spread out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Mean-preserving spread in simple terms?

In probability and statistics, a mean-preserving spread (MPS) is a change from one probability distribution A to another probability distribution B, where B is formed by spreading out one or more portions of A's probability density function or probability mass function while leaving the mean (the e…

Why does Mean-preserving spread 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 Mean-preserving spread?

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 Mean-preserving spread.

Tags

  • Decision theory
  • Theory of probability distributions

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