2. The length of time, in minutes, that a customer queues in a Post Office is a random variable, \(T\), with probability density function
$$\mathrm { f } ( t ) = \left\{ \begin{array} { c c }
c \left( 81 - t ^ { 2 } \right) & 0 \leqslant t \leqslant 9
0 & \text { otherwise }
\end{array} \right.$$
where \(c\) is a constant.
- Show that the value of \(c\) is \(\frac { 1 } { 486 }\)
- Show that the cumulative distribution function \(\mathrm { F } ( t )\) is given by
$$\mathrm { F } ( t ) = \left\{ \begin{array} { c c }
0 & t < 0
\frac { t } { 6 } - \frac { t ^ { 3 } } { 1458 } & 0 \leqslant t \leqslant 9
1 & t > 9
\end{array} \right.$$ - Find the probability that a customer will queue for longer than 3 minutes.
A customer has been queueing for 3 minutes.
- Find the probability that this customer will be queueing for at least 7 minutes.
Three customers are selected at random.
- Find the probability that exactly 2 of them had to queue for longer than 3 minutes.