Exam PProbability foundationsFree to read

Probability axioms and set identities

Three axioms generate every counting-free probability result on the exam, and inclusion-exclusion is the one identity that appears in some form on almost every sitting.

The formulas

Axioms
P(A)≥0,P(S)=1,P ⁣(⋃iAi)=∑iP(Ai) for disjoint AiP(A) \ge 0, \quad P(S) = 1, \quad P\!\left(\bigcup_i A_i\right) = \sum_i P(A_i) \text{ for disjoint } A_i
Complement
P(Ac)=1−P(A)P(A^{c}) = 1 - P(A)
Inclusion-exclusion (two sets)
P(A∪B)=P(A)+P(B)−P(A∩B)P(A \cup B) = P(A) + P(B) - P(A \cap B)
Inclusion-exclusion (three sets)
P(A∪B∪C)=∑P(A)−∑P(A∩B)+P(A∩B∩C)P(A\cup B\cup C) = \sum P(A) - \sum P(A\cap B) + P(A\cap B\cap C)
De Morgan
(A∪B)c=Ac∩Bc(A \cup B)^{c} = A^{c} \cap B^{c}

Where it comes from

  1. Write A∪BA \cup B as the disjoint union A∪(B∩Ac)A \cup (B \cap A^c); additivity gives P(A∪B)=P(A)+P(B∩Ac)P(A\cup B) = P(A) + P(B \cap A^c).
  2. Since B=(B∩A)∪(B∩Ac)B = (B\cap A) \cup (B \cap A^c) is also disjoint, P(B∩Ac)=P(B)−P(A∩B)P(B\cap A^c) = P(B) - P(A\cap B).
  3. Substituting gives inclusion-exclusion - the overlap was counted twice, so it is subtracted once.

Worked example

In a book of policies, 55% carry collision cover, 40% carry comprehensive cover, and 25% carry both. What proportion carries at least one of the two?

  1. 'At least one' is the union, so use P(A∪B)=P(A)+P(B)−P(A∩B)P(A\cup B) = P(A)+P(B)-P(A\cap B).
  2. P(A∪B)=0.55+0.40−0.25P(A \cup B) = 0.55 + 0.40 - 0.25.
  3. P(A∪B)=0.70P(A\cup B) = 0.70.
  4. As a check, the proportion with neither is 1−0.70=0.301 - 0.70 = 0.30.

Answer: 0.70

This answer is recomputed from the site’s own interest-theory and probability functions every time the test suite runs, so the page and the mathematics cannot drift apart.

Memory hooks

  • Add, add, subtract the overlap. Every 'at least one' question is that sentence.
  • When a question says 'neither', take the complement of the union - De Morgan turns it into a single subtraction.

Traps

  • Adding P(A) and P(B) without subtracting the intersection when the events are not disjoint.
  • Assuming disjoint and independent are the same thing. Disjoint events with positive probability are never independent.

Related

Drill this: the Exam P question bank has original questions on this topic, and today’s free round is open to everyone.