Math 2.0

Probability theory and stochastic processes Theorem

Law of the unconscious statistician

Builds on Expected valueLaw of a random variableProbability mass functionProbability density function

Statement

Let XX be a random variable on (Ω,ℱ,P)(\Omega, \mathcal{F}, P) with values in (E,ℰ)(E, \mathcal{E}) and with law μX\mu_X. Let g ⁣:E→ℝg \colon E \to \mathbb{R} be measurable. Then g(X)g(X) is integrable if and only if ∫E∣g∣ dμX<∞\int_E |g| \, d\mu_X < \infty. In that case, E[g(X)]=∫Eg(x) μX(dx).E[g(X)] = \int_E g(x) \, \mu_X(dx). In particular, if XX is discrete with mass function pp, then E[g(X)]=∑xg(x) p(x)E[g(X)] = \sum_x g(x) \, p(x). If XX is real with density ff, then E[g(X)]=∫−∞∞g(x)f(x) dxE[g(X)] = \int_{-\infty}^{\infty} g(x) f(x) \, dx.

Remarks

The formula also holds for g≥0g \ge 0 without any integrability condition, with both sides in [0,∞][0, \infty]. The proof checks the formula first for indicator functions g=1Bg = 1_B, where it says P(X∈B)=μX(B)P(X \in B) = \mu_X(B). Then it extends to simple, nonnegative and integrable gg. The point is that one does not need the law of g(X)g(X) to compute E[g(X)]E[g(X)].

History

The name refers to statisticians who use the formula as the definition of E[g(X)]E[g(X)]. They are "unconscious" that it is a theorem that needs a proof.

Reading path

To understand this page from the ground up, read these 49 pages in order. The foundations come first.

  1. Construction of the reals from Cauchy sequences concept
  2. Element definition
  3. Integers object
  4. Ordered field definition
  5. Proposition concept
  6. Random experiment concept
  7. Rational numbers object
  8. Real numbers object
  9. Set definition
  10. Ring of integers statement
  11. Disjunction definition
  12. Implication definition
  13. Predicate definition
  14. Ordered pair definition
  15. Union definition
  16. Sample space definition
  17. The rationals form a field statement
  18. Existential quantifier definition
  19. Universal quantifier definition
  20. Cartesian product definition
  21. Subset definition
  22. The rationals form an ordered field statement
  23. Uniqueness quantifier definition
  24. Binary relation definition
  25. Universal set definition
  26. Order on the reals definition
  27. Power set definition
  28. Complement definition
  29. Function definition
  30. Interval definition
  31. Injective function definition
  32. Preimage of a set definition
  33. Sigma-algebra definition
  34. Countable set definition
  35. Event definition
  36. Borel sigma-algebra definition
  37. Probability axioms concept
  38. Probability measure definition
  39. Probability distribution definition
  40. Probability space definition
  41. Random variable definition
  42. Cumulative distribution function definition
  43. Discrete random variable definition
  44. Law of a random variable definition
  45. Random variable with a density definition
  46. Probability mass function definition
  47. Expected value definition
  48. Probability density function definition
  49. Law of the unconscious statistician statement

Where this leads

33 pages build on this one.

Further reading

  1. Web https://en.wikipedia.org/wiki/Law_of_the_unconscious_statistician, Measure-theoretic formulation
About this page
Tag01ZWX875AT
URIm2://01ZWX875AT
Aliaseslotus, change-of-variables-formula-for-expectation
Kindstatement, theorem
WritingW0 stub
MSC60A05
StatusThis copy of the site has no build data. Run m2 status 01ZWX875AT.
UsesExpected value, Law of a random variable, Probability mass function, Probability density function
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