Answer :
To determine the relationship between events A and B, let's analyze the given probabilities:
1. Given Information:
- [tex]\( P(A|B) = 0.4 \)[/tex]
- [tex]\( P(A) = 0.4 \)[/tex]
2. Understanding Conditional Probability:
- [tex]\( P(A|B) \)[/tex] represents the probability of event A occurring given that event B has occurred.
- [tex]\( P(A) \)[/tex] represents the probability of event A occurring without any condition on event B.
3. Independence of Events:
- Two events A and B are considered independent if the occurrence of one event does not affect the probability of the occurrence of the other event.
- Mathematically, events A and B are independent if [tex]\( P(A|B) = P(A) \)[/tex].
4. Comparison:
- Here, [tex]\( P(A|B) = 0.4 \)[/tex] and [tex]\( P(A) = 0.4 \)[/tex].
Since [tex]\( P(A|B) = P(A) \)[/tex], it indicates that the occurrence of event B does not affect the probability of event A.
Conclusion:
- Option A is correct: Event A is not dependent on Event B.
1. Given Information:
- [tex]\( P(A|B) = 0.4 \)[/tex]
- [tex]\( P(A) = 0.4 \)[/tex]
2. Understanding Conditional Probability:
- [tex]\( P(A|B) \)[/tex] represents the probability of event A occurring given that event B has occurred.
- [tex]\( P(A) \)[/tex] represents the probability of event A occurring without any condition on event B.
3. Independence of Events:
- Two events A and B are considered independent if the occurrence of one event does not affect the probability of the occurrence of the other event.
- Mathematically, events A and B are independent if [tex]\( P(A|B) = P(A) \)[/tex].
4. Comparison:
- Here, [tex]\( P(A|B) = 0.4 \)[/tex] and [tex]\( P(A) = 0.4 \)[/tex].
Since [tex]\( P(A|B) = P(A) \)[/tex], it indicates that the occurrence of event B does not affect the probability of event A.
Conclusion:
- Option A is correct: Event A is not dependent on Event B.