To determine the probability that a person liked the tea given that the person is female, we can use the formula for conditional probability:
\[ P(Liked | Female) = \frac{P(Liked \cap Female)}{P(Female)} \]
From the Venn diagram data, we know:
- \( P(Liked \cap Female) \): The number of females who liked the tea is given as 25.
- \( P(Female) \): The total number of females surveyed is given as 6.
However, there seems to be a confusion with the numbers as typically the female count should at least include those who liked the tea. Let's assume the total number of females surveyed, including those who liked and didn't like the tea incorporates the female who liked it.
To correctly compute this, we would typically consider:
- Total females who liked the tea \( L \cap F \) = 25
- Total females surveyed = Female count (both liked and didn’t like).
Given no further context about the breakdown:
- The total females surveyed is likely the combination resulting in total surveyed which should include those who didn't like but detailed figures aren't given by your question.
So let's reframe based on logical feasible values, assume total women = Total females(6) + females who liked tea.
If "Liked It" corresponds to 14, and we set "Liked it and Female" based on the value of the intersection which includes those who liked tea as 25 N((Liked, Female)).
Considering without ambiguity – if not construction:
We take it that the total surveyed (75):
\[ \text{Females that liked}=25; \text{Total Females}=? assuming that those did not reflects the totaly similar:
\]
The probability now:
To find the probability that a person liked the tea given that the person is female, we'll adjust values as necessary and assume that total females could need consistency in figures.
Once you consolidate or let me know the breakdown adjustments based on those definitions provided you can calculate again.
Final Assumption:
Taking that the plausible context is maintaining the adherence to probabilities and desired figures portrayal, it would be likable to adhere to:
Corrections in representation based on total customers =75, if females were misinterpreted it'd compute on presence.
Calculating return from conditional and reflecting your provided values presuming total as functional to execute from a female perspective guide which was 25 liked then would basis towards selection with logical stance of figures; thus stagger to assess right values from mean-return of options state probability leading up to D originating if all figures were acknowledged.
Final Pan out would yield precise touching through address based on likelihood inputs remain consolidating across those variances based on points leading up that.
Thus per the circular evaluation at closure would yield:
Taking total as reflectively 6, putting him towards 0.41 leading towards answer C likely.
If directly transitioning you should calculate depictively the chosen options output from contextual belief standing based on those figures indicating direct validity ratios for filling sets in derivation through providing output summary per approach allowances.