An examination is attempted by $5000$ graduates, $2000$ post-graduates, and $1000$ doctorate holders. The probabilities that a graduate, a post-graduate, and a doctorate holder will pass the examination are $\frac{2}{3}$, $\frac{3}{4}$, and $\frac{4}{5}$ respectively. If one of the examinees passed the examination, then the probability that he is a post-graduate is:

$A$ bag contains $5$ balls of unknown colours. There are equal chances that out of these five balls,there may be $0, 1, 2, 3, 4,$ or $5$ red balls. $A$ ball is taken out from the bag at random and is found to be red. The probability that it is the only red ball in the bag is

$A$ box $A$ contains $2$ white,$3$ red and $2$ black balls. Another box $B$ contains $4$ white,$2$ red and $3$ black balls. If two balls are drawn at random,without replacement,from a randomly selected box and one ball turns out to be white while the other ball turns out to be red,then the probability that both balls are drawn from box $B$ is

$A$ signal which can be green or red with probability $\frac{4}{5}$ and $\frac{1}{5}$ respectively,is received by station $A$ and then transmitted to station $B$. The probability of each station receiving the signal correctly is $\frac{3}{4}$. If the signal received at station $B$ is green,then the probability that the original signal was green is

Box $I$ contains $30$ cards numbered $1$ to $30$ and Box $II$ contains $20$ cards numbered $31$ to $50$. $A$ box is selected at random and a card is drawn from it. The number on the card is found to be a non-prime number. The probability that the card was drawn from Box $I$ is

Suppose that the reliability of an $HIV$ test is specified as follows: Of people having $HIV$,$90\%$ of the tests detect the disease,but $10\%$ go undetected. Of people free of $HIV$,$99\%$ of the tests are judged $HIV$ negative,but $1\%$ are diagnosed as showing $HIV$ positive. From a large population of which only $0.1\%$ have $HIV$,one person is selected at random,given the $HIV$ test,and the pathologist reports him/her as $HIV$ positive. What is the probability that the person actually has $HIV$?