Probability – Conditional Probability & Multiplication Rule

Grade 11 Maths — Probability – Conditional Probability & Multiplication Rule: 25 practice questions with instant scoring and explanations.

1. Conditional probability P(A|B) is defined as:
2. The multiplication rule states: P(A ∩ B) =:
3. For independent events A and B, P(A|B) =:
4. Bayes' Theorem states:
5. If A and B are independent events, then P(A|B) =:
6. The law of total probability states: P(A) =:
7. If P(A) = 0.3, P(B) = 0.5, and A and B are independent, then P(A ∩ B) =:
8. If P(A|B) = 0.6 and P(B) = 0.4, then P(A ∩ B) =:
9. For two events A and B, if they are mutually exclusive, then P(A|B) =:
10. Conditional probability P(A|B) is NOT defined when:
11. If P(B|A) = 0.8, P(A) = 0.5, then P(A ∩ B) =:
12. The multiplication rule for three events: P(A ∩ B ∩ C) =:
13. If P(A) = 0.6 and P(B|A) = 0.5, what is P(A ∩ B)?
14. For independent events, the multiplication rule simplifies to:
15. P(B|A) can be calculated using:
16. If events are independent, then P(B|A) =:
17. In Bayes' theorem, P(A|B) depends on:
18. If A and B are exhaustive and mutually exclusive, then P(A ∪ B) =:
19. For mutually exclusive events A and B, P(A|B) =:
20. If P(A|B) = 0.7 and P(B) = 0.3, then P(A ∩ B) =:
21. The complement of conditional probability: P(A'|B) =:
22. If P(B|A) = 0.5 and P(A) = 0.8, is P(A ∩ B) = 0.4?
23. Given P(A) = 0.4, P(B) = 0.3, and P(A ∩ B) = 0.1, then P(A|B) =:
24. Bayes' theorem is particularly useful for:
25. If P(A) = 0.5, P(B) = 0.6, and A and B are independent, P(A ∪ B) = :