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 the children is a girl, find the probability that both children are girls.
(3) Upon observing one child who turns out to be a girl, find the probability that both children are girls.
(4) Given that one of the children is a girl, find the probability of observing 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, 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 .
Step 1. Let event A be "the older child is a girl." Then the sample points in A are {(G, B), (G, G)}. Let event B be "both children are girls." Then the sample points in B are {(G, G)}. The desired probability is the conditional probability .
Step 2. Let event C be "one of the children is a girl," which means at least one child is a girl. Then the sample points in C are {(B, G), (G, B), (G, G)}. Let event B be "both children are girls." Then the sample points in B are {(G, G)}. The desired probability is the conditional probability .
Step 3. "Observing a child who is a girl" is an observation event; denote it as event S. Let the events corresponding to family compositions GG, GB, BG, BB be , respectively. Under different family compositions, the probability of observing a girl is as follows: By the law of total probability, the probability of observing a girl is: The desired probability is . By Bayes' theorem:
Step 4. This problem asks for the probability of "observing a child who is a girl" (event S) given that "one of the children is a girl" (event C), i.e., . By the definition of conditional probability: If event S occurs (a girl is observed), then event C (at least one child is a girl) necessarily occurs. Therefore . From the computations in Steps 2 and 3, and .
Final answer
(1) (2) (3) (4)
Marking scheme
The following marking scheme is based on the official solution.
1. Checkpoints (max 7 pts total)
- Part (1) (1 pt)
- Correct result: . [1 pt]
- *(Note: If only the answer is given without working, this sub-part receives credit; if the reasoning is clearly erroneous but the answer happens to be correct, no credit is awarded.)*
- 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., ), or explicitly writes . [1 pt]
- Correct result: . [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 ," or the law of total probability is correctly applied to obtain . [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 may be awarded.)*
- Correct result: . [1 pt]
- Part (4) (2 pts)
- Logical derivation: Identifies that (i.e., "observing a girl" necessarily implies "at least one child is a girl") and thereby concludes ; or correctly constructs the ratio . [1 pt]
- Correct result: . [1 pt]
- Total (max 7)
2. Zero-credit items
- Merely copying the definition of conditional probability without substituting any specific values or performing any set analysis: 0 pts.
- Answering for Part (2) (confusing ordered vs. unordered outcomes, or conflating Parts (1) and (2)): 0 pts for that part.
- Answering for Part (3) (ignoring the observation probability and incorrectly assuming that any girl present is necessarily observed): 0 pts for that part.
- Answering for Part (4) (incorrectly treating "known that one child is a girl" and "observing a girl" as the same event): 0 pts for that part.
3. Deductions
- Arithmetic errors: Pure computational mistakes (e.g., incorrect fraction division): -1 pt.
- Carry-forward errors:
- If the logical formula in Part (4) is correct (e.g., ) but the final result is wrong due to incorrect values carried from Parts (2) or (3), no additional deduction is applied (only the points lost in the earlier parts are deducted); credit is awarded for correct logic.
- Missing justification:
- In Parts (3) or (4), if events are not defined or probability sources are not stated, and numbers are simply listed without readable logic: -1 pt.
- If an obvious probability fallacy appears, such as or : -1 pt.