Cumulative distribution function

Questions asking to find, write down, or use the CDF F(x) of a uniform distribution, or derive PDF from given CDF.

7 questions

Edexcel S2 2015 January Q2
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 \(\mathrm { E } \left( 3 X ^ { 2 } + 1 \right)\)
Edexcel S2 2018 Specimen Q2
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 \(\mathrm { E } \left( 3 X ^ { 2 } + 1 \right)\)
Edexcel S2 2010 January Q2
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 \(\mathrm { P } ( X = 1 )\).
Edexcel S2 2005 June Q2
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. \(\mathrm { P } ( 2.3 < X < 3.4 )\).
AQA S2 2012 June Q3
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. \(\mathrm { E } \left( 3 X ^ { 2 } \right)\).
Edexcel S2 Q3
3. 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: $$f ( x ) = \left\{ \begin{array} { l c } \frac { 1 } { 8 } , & - 4 \leq x \leq 4
0 , & \text { otherwise } \end{array} \right.$$
  1. Write down the name of this distribution.
  2. Define fully the cumulative distribution function \(\mathrm { F } ( x )\) of \(X\).
  3. Calculate the proportion of children making an error of less than \(15 \%\) according to this model.
  4. Give two reasons why this may not be a very suitable model.
OCR MEI Further Statistics B AS 2022 June Q2
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 \(b = 8\).