Questions: Select the correct answer from the drop-down menu. The probability that Jane will go to a ballgame (event A) on a Monday is 0.73, and the probability that Kate will go to a ballgame (event B) the same day is 0.61. The probability that Kate and Jane both go to the ballgame on Monday is 0.52. From the given scenario, we can conclude that events A and B are.

Select the correct answer from the drop-down menu.
The probability that Jane will go to a ballgame (event A) on a Monday is 0.73, and the probability that Kate will go to a ballgame (event B) the same day is 0.61. The probability that Kate and Jane both go to the ballgame on Monday is 0.52.

From the given scenario, we can conclude that events A and B are.
Transcript text: Select the correct answer from the drop-down menu. The probability that Jane will go to a ballgame (event $A$ ) on a Monday is 0.73 , and the probability that Kate will go to a ballgame (event $B$ ) the same day is 0.61 . The probability that Kate and Jane both go to the ballgame on Monday is 0.52 . From the given scenario, we can conclude that events $A$ and $B$ are $\square$
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Solution

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Solution Steps

Step 1: Calculate the Product of Individual Probabilities

To determine if events \( A \) and \( B \) are independent, we first calculate the product of their individual probabilities:

\[ P(A) = 0.73, \quad P(B) = 0.61 \]

The product of these probabilities is:

\[ P(A) \times P(B) = 0.73 \times 0.61 = 0.4453 \]

Step 2: Compare with the Probability of Intersection

Next, we compare the product \( P(A) \times P(B) \) with the given probability of both events occurring, \( P(A \cap B) \):

\[ P(A \cap B) = 0.52 \]

Step 3: Determine Independence

For events \( A \) and \( B \) to be independent, the following condition must hold:

\[ P(A \cap B) = P(A) \times P(B) \]

Substituting the values, we have:

\[ 0.52 \neq 0.4453 \]

Since \( P(A \cap B) \neq P(A) \times P(B) \), events \( A \) and \( B \) are not independent.

Final Answer

The events \( A \) and \( B \) are \(\boxed{\text{not independent}}\).

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