MathIsimple

Probability Theory – Problem 78: 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 them is a girl, find the probability that both children are girls. \underline{\qquad\qquad}

(3) Upon seeing one child who is a girl, find the probability that both children are girls. \underline{\qquad\qquad}

(4) Given that one of the children is a girl, find the probability of seeing a child who is a girl. \underline{\qquad\qquad}

Step-by-step solution

Let B denote a boy and G denote a girl. For a family with two children, without considering gender or birth order, the sample space is Ω={(B,B),(B,G),(G,B),(G,G)}\Omega = \{(B, B), (B, G), (G, B), (G, G)\}, where the first letter represents the older child and the second represents the younger child. Each outcome has equal probability 14\frac{1}{4}. (1) Let event AA be "the older child is a girl." Then AA contains the sample points {(G,B),(G,G)}\{(G, B), (G, G)\}. P(A)=24=12P(A) = \frac{2}{4} = \frac{1}{2} Let event BB be "both children are girls." Then BB contains the sample point {(G,G)}\{(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 CC be "one of them is a girl," meaning at least one child is a girl. Then CC contains the sample points {(B,G),(G,B),(G,G)}\{(B, G), (G, B), (G, G)\}. P(C)=34P(C) = \frac{3}{4} Let event BB be "both children are girls." Then BB contains the sample point {(G,G)}\{(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) "Seeing one child who is a girl" is an observational event, denoted as event SS. Let the events that the family composition is 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} The probability of seeing a girl under each family composition is: 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 seeing 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 part asks for the probability of "seeing a child who is a girl" (event SS) given "at least one child is a girl" (event CC), 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 SS occurs (a girl is seen), then event CC (at least one 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 is the marking scheme based on the official solution.

1. Checkpoints (max 7 pts total)

  • Part (1) (1 point)
  • Correct result: 1/21/2. [1 pt]
  • *(Note: If only the answer is given without work, credit is awarded for this part; if the logic is clearly wrong but the answer is forced, no credit.)*
  • Part (2) (2 points)
  • Key identification: Correctly identify that the conditioning event "at least one girl" corresponds to a sample space of size 3 (i.e., {GG,GB,BG}\{GG, GB, BG\}), or explicitly write P(C)=3/4P(C) = 3/4. [1 pt]
  • Correct result: 1/31/3. [1 pt]
  • Part (3) (2 points)
  • Observation model / total probability: The computation reflects the logic that "in a mixed-gender family (GB/BG), the probability of seeing a girl is 1/21/2," or correctly applies the law of total probability to compute P(S)=1/2P(S)=1/2. [1 pt]
  • *(Note: If the student uses an "independence" argument, i.e., stating that "seeing one child as a girl does not affect the gender distribution of the other child," and the logic is coherent, this point may be awarded.)*
  • Correct result: 1/21/2. [1 pt]
  • Part (4) (2 points)
  • Logical derivation: Identify that SCS \subseteq C (i.e., "seeing a girl" necessarily implies "at least one girl"), thereby determining P(SC)=P(S)P(S \cap C) = P(S); or correctly set up 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 formula P(AB)=P(AB)P(B)P(A|B) = \frac{P(AB)}{P(B)} without any concrete numerical substitution or set analysis earns 0 points.
  • Part (2) answer of 1/21/2 (confusing ordered vs. unordered, or confusing Part (1) with Part (2)) earns 0 points for that part.
  • Part (3) answer of 1/31/3 (ignoring the observation probability P(SGB)=1/2P(S|GB)=1/2, incorrectly assuming that having a girl guarantees she will be seen) earns 0 points for that part.
  • Part (4) answer of 11 (incorrectly believing "knowing there is a girl" and "seeing a girl" are the same event) earns 0 points for that part.

3. Deductions

  • Arithmetic error: Pure arithmetic mistakes (e.g., incorrect fraction division): -1 point.
  • Carry-forward error:
  • 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) leads to a wrong final result, no additional deduction (only the error in the preceding step is penalized); credit is awarded based on correct logic.
  • Missing logic:
  • In Part (3) or (4), if events are not defined or probability sources are not explained, and numbers are simply piled up making the logic unreadable: -1 point.
  • If an obvious probability fallacy appears such as P(A)>1P(A) > 1 or P(A)<0P(A) < 0: -1 point.
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