MathIsimple

Probability Theory – Problem 42: find the probability that both children are girls

Question

A family has two children whose genders and birth order are unknown.

(1) Given that the older child is a girl, find the probability that both children are girls. \underline{\qquad\qquad}

(2) Given that one of the children is a girl, find the probability that both children are girls. \underline{\qquad\qquad}

(3) Upon observing one child who turns out to be a girl, find the probability that both children are girls. \underline{\qquad\qquad}

(4) Given that at least one child is a girl, find the probability of observing a girl when one child is selected at random. \underline{\qquad\qquad}

Step-by-step solution

Let B denote a boy and G denote a girl. For a family with two children, disregarding gender and birth order, the sample space is Ω = {(B, B), (B, G), (G, B), (G, G)}, where the first letter represents the older child and the second letter represents the younger child. Each outcome is equally likely with probability 14\frac{1}{4}. (1) Let event A be "the older child is a girl." Then the sample points in A are {(G, B), (G, G)}. P(A)=24=12P(A) = \frac{2}{4} = \frac{1}{2} Let event B be "both children are girls." Then the sample points in B are {(G, G)}. P(B)=14P(B) = \frac{1}{4} The desired probability is the conditional probability P(BA)P(B|A). AB={(G,G)}A \cap B = \{(G, G)\} P(AB)=14P(A \cap B) = \frac{1}{4} P(BA)=P(AB)P(A)=1412=12P(B|A) = \frac{P(A \cap B)}{P(A)} = \frac{\frac{1}{4}}{\frac{1}{2}} = \frac{1}{2}

(2) Let event C be "one of the children is a girl," meaning at least one child is a girl. Then the sample points in C are {(B, G), (G, B), (G, G)}. P(C)=34P(C) = \frac{3}{4} Let event B be "both children are girls." Then the sample points in B are {(G, G)}. BC={(G,G)}B \cap C = \{(G, G)\} P(BC)=14P(B \cap C) = \frac{1}{4} The desired probability is the conditional probability P(BC)P(B|C). P(BC)=P(BC)P(C)=1434=13P(B|C) = \frac{P(B \cap C)}{P(C)} = \frac{\frac{1}{4}}{\frac{3}{4}} = \frac{1}{3}

(3) "Observing one child who turns out to be a girl" is an observation event; denote it as event S. Let the events corresponding to family compositions GG, GB, BG, BB be EGG,EGB,EBG,EBBE_{GG}, E_{GB}, E_{BG}, E_{BB}, respectively. P(EGG)=P(EGB)=P(EBG)=P(EBB)=14P(E_{GG}) = P(E_{GB}) = P(E_{BG}) = P(E_{BB}) = \frac{1}{4} Under each family composition, the probability of observing a girl is as follows: P(SEGG)=1P(S|E_{GG}) = 1 P(SEGB)=12P(S|E_{GB}) = \frac{1}{2} P(SEBG)=12P(S|E_{BG}) = \frac{1}{2} P(SEBB)=0P(S|E_{BB}) = 0 By the law of total probability, the probability of observing a girl P(S)P(S) is: P(S)=P(SEGG)P(EGG)+P(SEGB)P(EGB)+P(SEBG)P(EBG)+P(SEBB)P(EBB)P(S) = P(S|E_{GG})P(E_{GG}) + P(S|E_{GB})P(E_{GB}) + P(S|E_{BG})P(E_{BG}) + P(S|E_{BB})P(E_{BB}) P(S)=(1×14)+(12×14)+(12×14)+(0×14)=14+18+18=12P(S) = (1 \times \frac{1}{4}) + (\frac{1}{2} \times \frac{1}{4}) + (\frac{1}{2} \times \frac{1}{4}) + (0 \times \frac{1}{4}) = \frac{1}{4} + \frac{1}{8} + \frac{1}{8} = \frac{1}{2} The desired probability is P(EGGS)P(E_{GG}|S). By Bayes' theorem: P(EGGS)=P(SEGG)P(EGG)P(S)=1×1412=12P(E_{GG}|S) = \frac{P(S|E_{GG})P(E_{GG})}{P(S)} = \frac{1 \times \frac{1}{4}}{\frac{1}{2}} = \frac{1}{2}

(4) This problem asks for the probability of "observing a girl" (event S) given that "at least one child is a girl" (event C), i.e., P(SC)P(S|C). By the definition of conditional probability: P(SC)=P(SC)P(C)P(S|C) = \frac{P(S \cap C)}{P(C)} If event S occurs (a girl is observed), then event C (at least one child is a girl) necessarily occurs. Therefore SC=SS \cap C = S. P(SC)=P(S)P(C)P(S|C) = \frac{P(S)}{P(C)} From the computations in (2) and (3), P(C)=34P(C) = \frac{3}{4} and P(S)=12P(S) = \frac{1}{2}. P(SC)=1234=23P(S|C) = \frac{\frac{1}{2}}{\frac{3}{4}} = \frac{2}{3}

Final answer

(1) 12\frac{1}{2} (2) 13\frac{1}{3} (3) 12\frac{1}{2} (4) 23\frac{2}{3}

Marking scheme

The following rubric is based on the official solution.

1. Checkpoints (max 7 pts total)

  • Part (1) (1 pt)
  • Correct result: 1/21/2. [1 pt]
  • *(Note: If only the answer is given without working, full credit is awarded for this sub-part; if the reasoning is clearly flawed but the answer happens to be correct, no credit is given.)*
  • Part (2) (2 pts)
  • Key identification: Correctly identifies that the conditioning event "at least one girl" corresponds to a reduced sample space of size 3 (i.e., {GG,GB,BG}\{GG, GB, BG\}), or explicitly states P(C)=3/4P(C) = 3/4. [1 pt]
  • Correct result: 1/31/3. [1 pt]
  • Part (3) (2 pts)
  • Observation model / Law of total probability: The computation reflects the reasoning that in a mixed-gender family (GB/BG) the probability of observing a girl is 1/21/2, or the law of total probability is correctly applied to obtain P(S)=1/2P(S)=1/2. [1 pt]
  • *(Note: If the student uses an independence argument, i.e., argues that "observing one child to be a girl does not affect the gender distribution of the other child," and the logic is sound, this point is awarded.)*
  • Correct result: 1/21/2. [1 pt]
  • Part (4) (2 pts)
  • Logical derivation: Identifies that SCS \subseteq C (i.e., "observing a girl" necessarily implies "at least one child is a girl") and thereby concludes P(SC)=P(S)P(S \cap C) = P(S); or correctly constructs the ratio P(S)P(C)=1/23/4\frac{P(S)}{P(C)} = \frac{1/2}{3/4}. [1 pt]
  • Correct result: 2/32/3. [1 pt]
  • Total (max 7)

2. Zero-credit items

  • Merely copying the conditional probability definition P(AB)=P(AB)P(B)P(A|B) = \frac{P(AB)}{P(B)} without any concrete numerical substitution or set analysis earns 0 pts.
  • An answer of 1/21/2 for Part (2) (confusing ordered vs. unordered outcomes, or conflating Parts (1) and (2)) earns 0 pts for that part.
  • An answer of 1/31/3 for Part (3) (ignoring the observation probability P(SGB)=1/2P(S|GB)=1/2 and incorrectly assuming that having a girl guarantees she is observed) earns 0 pts for that part.
  • An answer of 11 for Part (4) (incorrectly treating "at least one child is a girl" and "observing a girl" as the same event) earns 0 pts for that part.

3. Deductions

  • Arithmetic errors: Pure computational mistakes (e.g., incorrect fraction division) incur a -1 pt deduction.
  • Carry-forward errors:
  • If the logical formula in Part (4) is correct (e.g., P(S)P(C)\frac{P(S)}{P(C)}) but an incorrect numerical value from Part (2) or (3) is carried forward, no additional deduction is applied (only the points lost in the earlier parts are forfeited); credit is given for correct logic.
  • Missing reasoning:
  • In Parts (3) or (4), if events are not defined or probability sources are not stated, and the work consists of unexplained numerical expressions rendering the logic unreadable, a -1 pt deduction applies.
  • If an obvious probability fallacy appears, such as P(A)>1P(A) > 1 or P(A)<0P(A) < 0, a -1 pt deduction applies.
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