The probability that event [tex]$A$[/tex] occurs is [tex]$12 \%$[/tex]. The probability that event [tex]$B$[/tex] occurs is [tex]$15 \%. The probability that both events occur is $[/tex]3 \%[tex]$.

What are the conditional probabilities of the two events?
Are $[/tex]A[tex]$ and $[/tex]B[tex]$ independent events?

Drag an answer into each empty box to complete the equations and sentence correctly.

$[/tex][tex]$
P(A \mid B) = \_\_
$[/tex][tex]$

The probability of $[/tex]A[tex]$ given $[/tex]B[tex]$ \_\_ as the probability of $[/tex]A[tex]$, so $[/tex]A[tex]$ and $[/tex]B[tex]$ \_\_ independent events.

Options:
- $[/tex]2 \%[tex]$
- $[/tex]4 \%[tex]$
- $[/tex]5 \%[tex]$
- $[/tex]20 \%[tex]$
- $[/tex]25 \%[tex]$
- $[/tex]36 \%[tex]$
- $[/tex]45 \%[tex]$
- $[/tex]80 \%$
- is the same
- is not the same
- are
- are not



Answer :

To address the given questions, let's first consider the values provided:

- Probability of event [tex]\( A \)[/tex] occurring, [tex]\( P(A) = 0.12 \)[/tex] or [tex]\( 12\% \)[/tex].
- Probability of event [tex]\( B \)[/tex] occurring, [tex]\( P(B) = 0.15 \)[/tex] or [tex]\( 15\% \)[/tex].
- Probability of both events [tex]\( A \)[/tex] and [tex]\( B \)[/tex] occurring, [tex]\( P(A \cap B) = 0.03 \)[/tex] or [tex]\( 3\% \)[/tex].

### 1. Conditional Probability [tex]\( P(A \mid B) \)[/tex]:
The conditional probability of [tex]\( A \)[/tex] given [tex]\( B \)[/tex] is calculated using the formula:
[tex]\[ P(A \mid B) = \frac{P(A \cap B)}{P(B)} \][/tex]

Substituting the given values:
[tex]\[ P(A \mid B) = \frac{0.03}{0.15} = 0.2 \text{ or } 20\% \][/tex]

### 2. Conditional Probability [tex]\( P(B \mid A) \)[/tex]:
The conditional probability of [tex]\( B \)[/tex] given [tex]\( A \)[/tex] is calculated using the formula:
[tex]\[ P(B \mid A) = \frac{P(A \cap B)}{P(A)} \][/tex]

Substituting the given values:
[tex]\[ P(B \mid A) = \frac{0.03}{0.12} = 0.25 \text{ or } 25\% \][/tex]

### 3. Independence of Events [tex]\( A \)[/tex] and [tex]\( B \)[/tex]:
Two events [tex]\( A \)[/tex] and [tex]\( B \)[/tex] are considered independent if and only if the probability of their intersection is equal to the product of their individual probabilities:
[tex]\[ P(A \cap B) = P(A) \cdot P(B) \][/tex]

Calculating the product of the individual probabilities:
[tex]\[ P(A) \cdot P(B) = 0.12 \cdot 0.15 = 0.018 \text{ or } 1.8\% \][/tex]

Comparing this with [tex]\( P(A \cap B) \)[/tex]:
[tex]\[ 0.03 \neq 0.018 \][/tex]

Since [tex]\( P(A \cap B) \)[/tex] is not equal to [tex]\( P(A) \cdot P(B) \)[/tex], events [tex]\( A \)[/tex] and [tex]\( B \)[/tex] are not independent.

### Final Answer:
Drag-and-drop responses:

- [tex]\( P(A \mid B) = 20\% \)[/tex]
- The probability of [tex]\( A \)[/tex] given [tex]\( B \)[/tex] is not the same as the probability of [tex]\( A \)[/tex], so [tex]\( A \)[/tex] and [tex]\( B \)[/tex] are not independent events.