Probability Fundamentals

Key Takeaways

  • Probability ranges from 0 (impossible) to 1 (certain); the sum of all probabilities in a sample space equals 1.
  • For mutually exclusive events: P(A or B) = P(A) + P(B).
  • For independent events: P(A and B) = P(A) × P(B).
  • Conditional probability P(A|B) = P(A and B) / P(B) is tested frequently.
  • Bayes' theorem relates conditional probabilities: P(A|B) = P(B|A)·P(A) / P(B).
  • Permutations (order matters) and combinations (order does not matter) count possible arrangements.
Last updated: March 2026

Probability Fundamentals

FE Exam Weight: Probability and Statistics accounts for 6-9 questions (~7% of the exam). These questions are often straightforward if you know the formulas.

Basic Probability Rules

Sample Space (S): The set of all possible outcomes.

Event (A): A subset of the sample space.

P(A)=Number of favorable outcomesTotal number of outcomesP(A) = \frac{\text{Number of favorable outcomes}}{\text{Total number of outcomes}}

Axioms of Probability

  1. 0 ≤ P(A) ≤ 1 for any event A
  2. P(S) = 1 (something must happen)
  3. P(A') = 1 - P(A) where A' is the complement of A

Addition Rule

  • General: P(A or B) = P(A) + P(B) - P(A and B)
  • Mutually exclusive events (A ∩ B = ∅): P(A or B) = P(A) + P(B)

Multiplication Rule

  • General: P(A and B) = P(A) · P(B|A)
  • Independent events: P(A and B) = P(A) · P(B)

Conditional Probability

The probability of A given that B has occurred: P(AB)=P(AB)P(B)P(A|B) = \frac{P(A \cap B)}{P(B)}

Example: A box contains 3 red and 7 blue balls. Two balls are drawn without replacement. What is the probability the second ball is red given the first was blue?

P(R₂|B₁) = 3/9 = 1/3 (3 red remain out of 9 total)

Bayes' Theorem

P(AB)=P(BA)P(A)P(B)P(A|B) = \frac{P(B|A) \cdot P(A)}{P(B)}

Extended form (with multiple hypotheses): P(AiB)=P(BAi)P(Ai)jP(BAj)P(Aj)P(A_i|B) = \frac{P(B|A_i) \cdot P(A_i)}{\sum_j P(B|A_j) \cdot P(A_j)}

Engineering Application: A manufacturing process produces 2% defective parts. A test detects defectives with 95% accuracy and falsely identifies good parts as defective 3% of the time. If a part tests positive, what is the probability it is actually defective?

P(D) = 0.02, P(+|D) = 0.95, P(+|D') = 0.03

P(D|+) = (0.95 × 0.02) / (0.95 × 0.02 + 0.03 × 0.98) = 0.019 / 0.0484 = 0.393

Even with a positive test, the part is only ~39% likely to be defective because defectives are rare.

Counting Methods

Permutations (Order Matters)

P(n,r)=n!(nr)!P(n, r) = \frac{n!}{(n-r)!}

Example: How many ways can 3 people be selected for President, VP, and Treasurer from 10 candidates? P(10, 3) = 10!/(10-3)! = 10 × 9 × 8 = 720

Combinations (Order Does Not Matter)

C(n,r)=(nr)=n!r!(nr)!C(n, r) = \binom{n}{r} = \frac{n!}{r!(n-r)!}

Example: How many ways can a committee of 3 be chosen from 10 people? C(10, 3) = 10!/(3!·7!) = 120

Test Your Knowledge

Events A and B are independent with P(A) = 0.3 and P(B) = 0.4. What is P(A and B)?

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B
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Test Your Knowledge

A bag has 5 red and 3 blue marbles. Two marbles are drawn without replacement. What is the probability both are red?

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B
C
D