**Dependent Events**

When two events A and B are said to be dependent, it means that the occurrence of one event affects the probability of the occurrence of the other event. In other words, the probability of event B happening depends on whether or not event A has already occurred.

**Independent Events**

On the other hand, if two events A and B are independent, it means that the occurrence or non-occurrence of one event does not affect the probability of the occurrence of the other event. In this case, the probability of event B happening remains the same regardless of whether or not event A has already occurred.

**Explanation of the Answer**

The given statement states that P(A ∩ B) = P(A) * P(B), which means that the probability of both events A and B happening together is equal to the product of their individual probabilities. If this condition holds true, it implies that events A and B are independent.

To understand this concept further, let's consider an example:

Suppose event A represents the event of flipping heads on a fair coin, and event B represents the event of rolling a 4 on a fair six-sided die.

- P(A) = 1/2, since the probability of flipping heads on a fair coin is 1/2.
- P(B) = 1/6, since the probability of rolling a 4 on a fair six-sided die is 1/6.
- P(A ∩ B) = P(A) * P(B) = (1/2) * (1/6) = 1/12.

In this example, the probability of flipping heads on a coin and rolling a 4 on a die are independent events, as the probability of one event does not affect the probability of the other event. Therefore, the given condition P(A ∩ B) = P(A) * P(B) holds true, and the answer is option B: Dependent.

B