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.
(2) Given that one of them is a girl, find the probability that both children are girls.
(3) Upon seeing one child who is a girl, find the probability that both children are girls.
(4) Given that one of the children is a girl, find the probability of seeing a child who is a girl.
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 , where the first letter represents the older child and the second represents the younger child. Each outcome has equal probability . (1) Let event be "the older child is a girl." Then contains the sample points . Let event be "both children are girls." Then contains the sample point . The desired probability is the conditional probability .
(2) Let event be "one of them is a girl," meaning at least one child is a girl. Then contains the sample points . Let event be "both children are girls." Then contains the sample point . The desired probability is the conditional probability .
(3) "Seeing one child who is a girl" is an observational event, denoted as event . Let the events that the family composition is GG, GB, BG, BB be respectively. The probability of seeing a girl under each family composition is: By the law of total probability, the probability of seeing a girl is: The desired probability is . By Bayes' theorem:
(4) This part asks for the probability of "seeing a child who is a girl" (event ) given "at least one child is a girl" (event ), i.e., . By the definition of conditional probability: If event occurs (a girl is seen), then event (at least one girl) necessarily occurs. Therefore . From the computations in (2) and (3), and .
Final answer
(1) (2) (3) (4)
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 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., ), or explicitly write . [1 pt]
- Correct result: . [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 ," or correctly applies the law of total probability to compute . [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 pt]
- Part (4) (2 points)
- Logical derivation: Identify that (i.e., "seeing a girl" necessarily implies "at least one girl"), thereby determining ; or correctly set up the ratio . [1 pt]
- Correct result: . [1 pt]
- Total (max 7)
2. Zero-credit items
- Merely copying the conditional probability definition formula without any concrete numerical substitution or set analysis earns 0 points.
- Part (2) answer of (confusing ordered vs. unordered, or confusing Part (1) with Part (2)) earns 0 points for that part.
- Part (3) answer of (ignoring the observation probability , incorrectly assuming that having a girl guarantees she will be seen) earns 0 points for that part.
- Part (4) answer of (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., ) 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 or : -1 point.