Cumulative distribution function

2. A continuous random variable \(X\) has cumulative distribution function $$\mathrm { F } ( x ) = \left\{ \begin{array} { c c } 0 & x < 1 \\ \frac { 1 } { 5 } ( x - 1 ) & 1 \leqslant x \leqslant 6 \\ 1 & x > 6 \end{array} \right.$$

1. Find \(\mathrm { P } ( X > 4 )\)
2. Write down the value of \(\mathrm { P } ( X \neq 4 )\)
3. Find the probability density function of \(X\), specifying it for all values of \(X\)
4. Write down the value of \(\mathrm { E } ( X )\)
5. Find \(\operatorname { Var } ( X )\)
6. Hence or otherwise find \(\mathrm { E } \left( 3 X ^ { 2 } + 1 \right)\)

2. A continuous random variable \(X\) has cumulative distribution function $$\mathrm { F } ( x ) = \left\{ \begin{array} { c c } 0 & x < 1 \\ \frac { 1 } { 5 } ( x - 1 ) & 1 \leqslant x \leqslant 6 \\ 1 & x > 6 \end{array} \right.$$

1. Find \(\mathrm { P } ( X > 4 )\)
2. Write down the value of \(\mathrm { P } ( X \neq 4 )\)
3. Find the probability density function of \(X\), specifying it for all values of \(x\)
4. Write down the value of \(\mathrm { E } ( X )\)
5. Find \(\operatorname { Var } ( X )\)
6. Hence or otherwise find \(\mathrm { E } \left( 3 X ^ { 2 } + 1 \right)\)

2. A continuous random variable \(X\) has cumulative distribution function $$\mathrm { F } ( x ) = \begin{cases} 0 , & x < - 2 \\ \frac { x + 2 } { 6 } , & - 2 \leqslant x \leqslant 4 \\ 1 , & x > 4 \end{cases}$$

1. Find \(\mathrm { P } ( X < 0 )\).
2. Find the probability density function \(\mathrm { f } ( x )\) of \(X\).
3. Write down the name of the distribution of \(X\).
4. Find the mean and the variance of \(X\).
5. Write down the value of \(\mathrm { P } ( X = 1 )\).

2. The continuous random variable \(X\) is uniformly distributed over the interval \([ 2,6 ]\).

1. Write down the probability density function \(\mathrm { f } ( x )\). Find
2. \(\mathrm { E } ( X )\),
3. \(\operatorname { Var } ( X )\),
4. the cumulative distribution function of \(X\), for all \(x\),
5. \(\mathrm { P } ( 2.3 < X < 3.4 )\).

3 The continuous random variable \(X\) has a cumulative distribution function defined by $$\mathrm { F } ( x ) = \left\{ \begin{array} { c l } 0 & x < - 5 \\ \frac { x + 5 } { 20 } & - 5 \leqslant x \leqslant 15 \\ 1 & x > 15 \end{array} \right.$$

1. Show that, for \(- 5 \leqslant x \leqslant 15\), the probability density function, \(\mathrm { f } ( x )\), of \(X\) is given by \(\mathrm { f } ( x ) = \frac { 1 } { 20 }\).
   (1 mark)
2. Find:
   1. \(\mathrm { P } ( X \geqslant 7 )\);
   2. \(\mathrm { P } ( X \neq 7 )\);
   3. \(\mathrm { E } ( X )\);
   4. \(\mathrm { E } \left( 3 X ^ { 2 } \right)\).

2 The continuous random variable \(X\) has cumulative distribution function given by \(F ( x ) = \begin{cases} 0 & x < a , \\ \frac { x - a } { b - a } & a \leqslant x \leqslant b , \\ 1 & x > b , \end{cases}\) where \(a\) and \(b\) are constants with \(0 < \mathrm { a } < \mathrm { b }\).

1. Find \(\mathrm { P } \left( \mathrm { X } < \frac { 1 } { 2 } ( \mathrm { a } + \mathrm { b } ) \right)\).
2. Sketch the graph of the probability density function of \(X\).
3. Find the variance of \(X\) when \(a = 2\) and \(b = 8\).

Jean catches a bus to work every morning. According to the timetable the bus is due at 8 a.m., but Jean knows that the bus can arrive at a random time between five minutes early and 9 minutes late. The random variable X represents the time, in minutes, after 7.55 a.m. when the bus arrives.

1. Suggest a suitable model for the distribution of X and specify it fully. [2]
2. Calculate the mean time of arrival of the bus. [3]
3. Find the cumulative distribution function of X. [4]

Jean will be late for work if the bus arrives after 8.05 a.m.

1. Find the probability that Jean is late for work. [2]

A class of children are each asked to draw a line that they think is 10 cm long without using a ruler. The teacher models how many centimetres each child's line is longer than 10 cm by the random variable \(X\) and believes that \(X\) has the following probability density function: $$f(x) = \begin{cases} \frac{1}{8}, & -4 \leq x \leq 4, \\ 0, & \text{otherwise}. \end{cases}$$

1. Write down the name of this distribution. [1]
2. Define fully the cumulative distribution function F(x) of \(X\). [4]
3. Calculate the proportion of children making an error of less than 15\% according to this model. [3]
4. Give two reasons why this may not be a very suitable model. [2]