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ISC 2027
All chaptersMaths · Unit 7

Probability

6 articles23 formulas31 ways the board asks it
MATConditional Probability & Independence

Conditional Probability & the Multiplication Theorem

Conditional probability P(A∣B)P(A\mid B) is the probability of event AA given that event BB has already occurred, found by restricting the sample space to BB. Rearranging its definition gives the multiplication theorem P(A∩B)=P(B) P(A∣B)P(A\cap B)=P(B)\,P(A\mid B), the backbone of "draw without replacement" and "given that" problems that appear every year.

Definition of conditional probability
P(A∣B)=P(A∩B)P(B),P(B)≠0P(A \mid B) = \dfrac{P(A \cap B)}{P(B)}, \quad P(B) \ne 0
P(A∣B)P(A\mid B) = probability of AA given BB has occurred; P(A∩B)P(A\cap B) = probability both occur. Requires P(B)>0P(B) > 0.
Multiplication theorem of probability
P(A∩B)=P(B) P(A∣B)=P(A) P(B∣A)P(A \cap B) = P(B)\,P(A \mid B) = P(A)\,P(B \mid A)
Valid for any two events with positive probability; choose the conditioning order that matches the order of the experiment.
Multiplication for three events (chain rule)
P(A∩B∩C)=P(A) P(B∣A) P(C∣A∩B)P(A \cap B \cap C) = P(A)\,P(B \mid A)\,P(C \mid A \cap B)
Used for successive draws without replacement; each factor conditions on all previous outcomes.
Successive draws without replacement
P(both red)=rn⋅r−1n−1P(\text{both red}) = \dfrac{r}{n}\cdot\dfrac{r-1}{n-1}
rr = number of red balls, nn = total balls; the numerator and denominator each drop by 11 on the second draw because no ball is replaced.
  • Reduced sample space view: P(A∣B)P(A\mid B) counts favourable outcomes for AA only among the outcomes already in BB.
  • Key properties: 0≤P(A∣B)≤10 \le P(A\mid B) \le 1, P(B∣B)=1P(B\mid B)=1, and P(A′∣B)=1−P(A∣B)P(A'\mid B) = 1 - P(A\mid B).
  • For drawing "one after another without replacement", multiply the probabilities of each stage, updating the counts after each draw.
  • In the two-children "given at least one boy" problem the reduced sample space is {BB,BG,GB}\{BB, BG, GB\} (3 equally likely cases), giving P(two boys∣at least one boy)=13P(\text{two boys}\mid \text{at least one boy}) = \dfrac{1}{3}, not 12\dfrac{1}{2}.
  • "Given that the card is a face card" restricts to the 1212 face cards; for example P(King∣face card)=412=13P(\text{King}\mid\text{face card}) = \dfrac{4}{12} = \dfrac{1}{3}.
  • Identify the conditioning event (BB) carefully — it is the information stated after the words "given that".
  • P(A∣B)P(A\mid B) and P(B∣A)P(B\mid A) are generally different; do not interchange them.
Worked example · 2 marks
Evaluate P(A∪B)P(A\cup B) given that 2P(A)=P(B)=5132P(A) = P(B) = \dfrac{5}{13} and P(A∣B)=25P(A\mid B) = \dfrac{2}{5}.
  1. Read off the two marginals: P(B)=513P(B) = \dfrac{5}{13}, and since 2P(A)=5132P(A) = \dfrac{5}{13}, P(A)=526P(A) = \dfrac{5}{26}.
  2. Turn the conditional into an intersection with the multiplication theorem: P(A∩B)=P(A∣B) P(B)=25×513=213P(A\cap B) = P(A\mid B)\,P(B) = \dfrac{2}{5}\times\dfrac{5}{13} = \dfrac{2}{13}.
  3. Addition theorem: P(A∪B)=P(A)+P(B)−P(A∩B)P(A\cup B) = P(A) + P(B) - P(A\cap B).
  4. Over a common denominator of 2626: 526+1026−426\dfrac{5}{26} + \dfrac{10}{26} - \dfrac{4}{26}.
Where the marks go
  • Confusing P(A∩B)P(A\cap B) (both happen) with P(A∣B)P(A\mid B) (one given the other) — the conditional divides by P(B)P(B).
  • Treating without-replacement draws as if the second draw had the same denominator as the first.
  • In "at least one shows a 3" type dice problems, forgetting to restrict the sample space to the conditioning event before counting favourable cases.
  • Reversing the multiplication order so that the conditioning does not match the actual sequence of the experiment.
How the board asks it
  • Applicationmultiplication theorem; drawing without replacement4 mkAsked 2025
    A bag contains 55 white and 77 black balls. Two balls are drawn one after the other without replacement. Find the probability that both balls drawn are black.
  • Numericaldefinition of conditional probability2 mkAsked 2024
    If P(A)=0.6P(A) = 0.6, P(B)=0.5P(B) = 0.5 and P(A∩B)=0.3P(A \cap B) = 0.3, find P(A∣B)P(A \mid B) and P(B∣A)P(B \mid A).
  • Multiple choicedefinition of conditional probability1 mkAsked 2026
    If AA and BB are events such that P(B)=0.4P(B) = 0.4 and P(A∩B)=0.16P(A \cap B) = 0.16, then P(A∣B)P(A \mid B) equals: (a) 0.160.16 (b) 0.40.4 (c) 0.640.64 (d) 0.240.24.
  • Numericalmultiplication theorem for three events1 mkAsked 2026
    An urn contains 44 red and 66 green balls. Three balls are drawn successively without replacement. Find the probability that the first is red, the second is green and the third is red.
  • Give reasonsreduced sample space view
    A die is thrown twice and the sum of the numbers appearing is observed to be 88. Find the conditional probability that the number 55 has appeared at least once, clearly stating the reduced sample space.
  • Assertion–Reasonmutual exclusivity is not what makes P(A∣B)=P(B∣A)P(A\mid B) = P(B\mid A)1 mkAsked 2025
    Assertion: for events AA and BB with n(A)=n(B)n(A) = n(B), P(A∣B)=P(B∣A)P(A\mid B) = P(B\mid A). Reason: AA and BB are mutually exclusive.

Practise this topic

Written for Sublevo. Question text quoted anywhere in these notes is the Council’s and carries its year and paper; the board’s own diagrams are not reproduced.