When we want to know the chance that both events A and B happen, we use:
This tells us how to find the chance that two events overlap. It’s especially useful when we know a conditional probability.
Let A = first stage meets specs (P(A) = 0.90)
B = second stage meets specs given A (P(B|A) = 0.95)
Interpretation: There’s an 85.5% chance that both stages meet specifications. The more steps, the lower the chance unless each step is very reliable!
Out of 20 students, 10 submitted the homework. Among them, 3 got an A. What is P(A | submitted)?
Interpretation: Given that a student submitted, 30% of them earned an A. Looking at the whole class, 15% of all students both submitted and earned an A.
60% of packages are sent via Air (A), and 90% of those arrive on time (T). Find P(package is Air and On Time).
Interpretation: More than half of all packages are both sent by Air and arrive on time.
If event B can happen under multiple conditions, we combine them using:
20% of chips are exposed to high contamination (H).
  If contaminated: P(Failure | H) = 0.10
  If clean: P(Failure | H′) = 0.005
Interpretation: The total failure rate is a weighted average based on contamination level.
More generally, if events E₁, E₂, ..., Eₖ are mutually exclusive and exhaustive:
This breaks down B into smaller parts that can be calculated separately and summed.
Out of 30 students, 12 completed the project. Among those, 5 received an A grade. What is:
P(A | completed) = 5 / 12 = 0.4167
P(completed) = 12 / 30 = 0.40
P(A ∩ completed) = 0.4167 × 0.40 = 0.1667