$\begin{array}{1 1} 5/24 \\ 5/34 \\ 7/24 \\ 7/34 \end{array} $

Want to ask us a question? Click here

Browse Questions

Ad |

0 votes

0 votes

- Given $E_1, E_2, E_3.....E_n$ are mutually exclusive and exhaustive events, we can find the conditional probability $P(E_i|A)$ for any event A associated w/ $E_i$ using the Bayes theorem as follows: \(\;P(E_i/A)\)=\(\large \frac{P(E_i)P(A/E_i)}{\sum_{i=1}^{n}\;P(E_i)P(A/E_i)}\)

Let $E_1$ be the event that the machine A is defective. P ($E_1$) = 1%.

Let $E_2$ be the event that the machine B is defective. P ($E_2$) = 5%.

Let $E_3$ be the event that the machine C is defective. P ($E_3$) = 7%.

Let A: be the event that an item chosen at random was an defective item.

P (that the defective item came from A) = P (A|$E_1$) = 50%.

P (that the defective item came from B) = P (A|$E_2$) = 30%.

P (that the defective item came from C) = P (A|$E_3$) = 20%.

We need to calculate that if a defective item is produced what is the probability that it came from A?

We can use Baye's theorem, according to which $P(E_1|A) = \large\frac{P(E_1)(P(A|E_1)}{P(E_1)P(A|E_1) + P(E_2)P(A|E_2) + P(E_3)(PA|E_3)}$

Therefore P(A|$E_1$) = $\large \frac{0.05 \times 0.1}{0.05 \times 0.1 + 0.30 \times 0.05 + 0.20 \times 0.07} = \frac{0.005}{0.005+0.0150+0.014} = \frac{0.005}{0.034} = \frac{5}{34}$

Ask Question

Take Test

x

JEE MAIN, CBSE, AIPMT Mobile and Tablet App

The ultimate mobile app to help you crack your examinations

...