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) $:
$$ P(E_1|A) = \frac{P(E_1 \cap A)}{P(A)} = \frac{\frac{1}{3}}{\frac{2}{3}} = \frac{1}{2}. $$
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:
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.
In a practical examination, the following pedigree chart was given as a spotter for identification. The students identify the given pedigree chart as 