Given:
We want to find \(P(E_1|A)\). We can use Bayes' theorem:
\(P(E_1|A) = \frac{P(A|E_1) \cdot P(E_1)}{P(A)}\)
We know \(P(E_1) = \frac{1}{2}\). We need to find \(P(A|E_1)\) and \(P(A)\).
Since \(E_1\) and \(E_2\) form a partition:
\(P(A) = P(A \cap E_1) + P(A \cap E_2)\)
\(P(A) = P(A|E_1)P(E_1) + P(A|E_2)P(E_2)\)
We know \(P(A|E_2) = \frac{2}{3}\) and \(P(E_2) = \frac{1}{2}\), so:
\(P(A \cap E_2) = (\frac{2}{3})(\frac{1}{2}) = \frac{1}{3}\)
Also, we are given \(P(E_2|A) = \frac{1}{2}\). Using the definition of conditional probability:
\(P(E_2|A) = \frac{P(E_2 \cap A)}{P(A)}\)
\(\frac{1}{2} = \frac{\frac{1}{3}}{P(A)}\)
\(P(A) = \frac{2}{3}\)
Now we have:
\(P(A) = P(A|E_1)P(E_1) + P(A|E_2)P(E_2)\)
\(\frac{2}{3} = P(A|E_1)(\frac{1}{2}) + (\frac{2}{3})(\frac{1}{2})\)
\(\frac{2}{3} = P(A|E_1)(\frac{1}{2}) + \frac{1}{3}\)
\(P(A|E_1)(\frac{1}{2}) = \frac{1}{3}\)
\(P(A|E_1) = \frac{2}{3}\)
Finally, we can calculate \(P(E_1|A)\):
\(P(E_1|A) = \frac{P(A|E_1) \cdot P(E_1)}{P(A)}\)
\(P(E_1|A) = \frac{(\frac{2}{3}) \cdot (\frac{1}{2})}{\frac{2}{3}}\)
\(P(E_1|A) = \frac{\frac{1}{3}}{\frac{2}{3}}\)
\(P(E_1|A) = \frac{1}{2}\)
We are given:
$$ P(E_1) = P(E_2) = \frac{1}{2}, \quad P(E_2|A) = \frac{P(E_2 \cap A)}{P(A)} = \frac{1}{2}, \quad P(A|E_2) = \frac{P(A \cap E_2)}{P(E_2)} = \frac{2}{3}. $$
We want to find $ P(E_1|A) = \frac{P(E_1 \cap A)}{P(A)} $. From $ P(A|E_2) = \frac{2}{3} $, we calculate:
$$ P(A \cap E_2) = P(A|E_2) P(E_2) = \frac{2}{3} \cdot \frac{1}{2} = \frac{1}{3}. $$
From $ P(E_2|A) = \frac{1}{2} $, we know:
$$ P(E_2 \cap A) = \frac{1}{2} P(A). $$
Equating the two expressions for $ P(E_2 \cap A) $:
$$ \frac{1}{3} = \frac{1}{2} P(A) \implies P(A) = \frac{2}{3}. $$
Since $ E_1 $ and $ E_2 $ form a partition, $ A = (A \cap E_1) \cup (A \cap E_2) $. Thus:
$$ P(A) = P(A \cap E_1) + P(A \cap E_2). $$
Substitute $ P(A) = \frac{2}{3} $ and $ P(A \cap E_2) = \frac{1}{3} $:
$$ \frac{2}{3} = P(A \cap E_1) + \frac{1}{3} \implies P(A \cap E_1) = \frac{1}{3}. $$
Finally, calculate $ P(E_1|A) $:
$$ P(E_1|A) = \frac{P(E_1 \cap A)}{P(A)} = \frac{\frac{1}{3}}{\frac{2}{3}} = \frac{1}{2}. $$
A gardener wanted to plant vegetables in his garden. Hence he bought 10 seeds of brinjal plant, 12 seeds of cabbage plant, and 8 seeds of radish plant. The shopkeeper assured him of germination probabilities of brinjal, cabbage, and radish to be 25%, 35%, and 40% respectively. But before he could plant the seeds, they got mixed up in the bag and he had to sow them randomly.
Given three identical bags each containing 10 balls, whose colours are as follows:
Bag I | 3 Red | 2 Blue | 5 Green |
Bag II | 4 Red | 3 Blue | 3 Green |
Bag III | 5 Red | 1 Blue | 4 Green |
A person chooses a bag at random and takes out a ball. If the ball is Red, the probability that it is from Bag I is $ p $ and if the ball is Green, the probability that it is from Bag III is $ q $, then the value of $ \frac{1}{p} + \frac{1}{q} $ is: