5.03f Relate pdf-cdf: medians and percentiles

234 questions

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Edexcel FS2 2021 June Q3
10 marks Standard +0.3
  1. The continuous random variable \(X\) has cumulative distribution function given by
$$\mathrm { F } ( x ) = \left\{ \begin{array} { c r } 0 & x < 2 \\ 1.25 - \frac { 2.5 } { x } & 2 \leqslant x \leqslant 10 \\ 1 & x > 10 \end{array} \right.$$
  1. Find \(\mathrm { P } ( \{ X < 5 \} \cup \{ X > 8 \} )\)
  2. Find the median of \(X\).
  3. Find \(\mathrm { E } \left( X ^ { 2 } \right)\)
    1. Sketch the probability density function of \(X\).
    2. Describe the skewness of the distribution of \(X\).
CAIE S2 2019 June Q6
9 marks Standard +0.3
  1. Show that \(b = \frac { a } { a - 1 }\).
  2. Given that the median of \(X\) is \(\frac { 3 } { 2 }\), find the values of \(a\) and \(b\).
  3. Use your values of \(a\) and \(b\) from part (ii) to find \(\mathrm { E } ( X )\).
CAIE Further Paper 4 2023 November Q4
9 marks Standard +0.3
  1. Given that \(\mathrm { P } ( X \leqslant 2 ) = \frac { 1 } { 3 }\), show that \(m = \frac { 1 } { 6 }\) and find the values of \(k\) and \(c\).
  2. Find the exact numerical value of the interquartile range of \(X\).
AQA S2 2009 January Q4
6 marks Moderate -0.3
4 The continuous random variable \(X\) has the cumulative distribution function $$\mathrm { F } ( x ) = \left\{ \begin{array} { c c } 0 & x < - c \\ \frac { x + c } { 4 c } & - c \leqslant x \leqslant 3 c \\ 1 & x > 3 c \end{array} \right.$$ where \(c\) is a positive constant.
  1. Determine \(\mathrm { P } \left( - \frac { 3 c } { 4 } < X < \frac { 3 c } { 4 } \right)\).
  2. Show that the probability density function, \(\mathrm { f } ( x )\), of \(X\) is $$f ( x ) = \left\{ \begin{array} { c c } \frac { 1 } { 4 c } & - c \leqslant x \leqslant 3 c \\ 0 & \text { otherwise } \end{array} \right.$$
  3. Hence, or otherwise, find expressions, in terms of \(c\), for:
    1. \(\mathrm { E } ( X )\);
    2. \(\operatorname { Var } ( X )\).
AQA S2 2009 January Q7
12 marks Standard +0.3
7 The continuous random variable \(X\) has the probability density function given by $$f ( x ) = \left\{ \begin{array} { c c } \frac { 1 } { 16 } x ^ { 3 } & 0 \leqslant x \leqslant 2 \\ \frac { 1 } { 6 } ( 5 - x ) & 2 \leqslant x \leqslant 5 \\ 0 & \text { otherwise } \end{array} \right.$$
  1. Sketch the graph of f.
  2. Prove that the cumulative distribution function of \(X\) for \(2 \leqslant x \leqslant 5\) can be written in the form $$\mathrm { F } ( x ) = 1 - \frac { 1 } { 12 } ( 5 - x ) ^ { 2 }$$
  3. Hence, or otherwise, determine \(\mathrm { P } ( X \geqslant 3 \mid X \leqslant 4 )\).
AQA S2 2009 June Q4
12 marks Standard +0.3
4 The continuous random variable \(X\) has probability density function given by $$f ( x ) = \left\{ \begin{array} { c c } \frac { 1 } { 2 } & 0 \leqslant x \leqslant 1 \\ \frac { 3 - x } { 4 } & 1 \leqslant x \leqslant 3 \\ 0 & \text { otherwise } \end{array} \right.$$
  1. Sketch the graph of f.
  2. Explain why the value of \(\eta\), the median of \(X\), is 1 .
  3. Show that the value of \(\mu\), the mean of \(X\), is \(\frac { 13 } { 12 }\).
  4. Find \(\mathrm { P } ( X < 3 \mu - \eta )\).
AQA Further AS Paper 2 Statistics 2024 June Q6
11 marks Challenging +1.2
6 The continuous random variable \(X\) has probability density function $$f ( x ) = \begin{cases} \frac { 3 x } { 44 } + \frac { 1 } { 22 } & 1 \leq x \leq 5 \\ 0 & \text { otherwise } \end{cases}$$ 6
  1. Find \(\mathrm { P } ( X > 2 )\) [0pt] [2 marks]
    6
  2. Find the upper quartile of \(X\) Give your answer to two decimal places.
    6
  3. Find \(\operatorname { Var } \left( 44 X ^ { - 3 } \right)\) Give your answer to three decimal places.
AQA Further Paper 3 Statistics 2019 June Q5
7 marks Standard +0.3
5 An insurance company models the claims it pays out in pounds \(( \pounds )\) with a random variable \(X\) which has probability density function $$f ( x ) = \begin{cases} \frac { k } { x } & 1 < x < a \\ 0 & \text { otherwise } \end{cases}$$ 5
  1. The median claim is \(\pounds 200\) Show that \(k = \frac { 1 } { 2 \ln 200 }\) 5
  2. Find \(\mathrm { P } ( X < 2000 )\), giving your answer to three significant figures.
    5
  3. The insurance company finds that the maximum possible claim is \(\pounds 2000\) and they decide to refine their probability density function. Suggest how this could be done.
AQA Further Paper 3 Statistics 2023 June Q8
14 marks Standard +0.3
8 The continuous random variable \(X\) has probability density function $$f ( x ) = \begin{cases} k \sin 2 x & 0 \leq x \leq \frac { \pi } { 6 } \\ 0 & \text { otherwise } \end{cases}$$ where \(k\) is a constant. 8
  1. Show that \(k = 4\) 8
  2. Find the cumulative distribution function \(\mathrm { F } ( x )\) 8
  3. Find the median of \(X\), giving your answer to three significant figures. 8
  4. Find the mean of \(X\) giving your answer in the form \(\frac { 1 } { a } ( b \sqrt { 3 } - \pi )\) where \(a\) and \(b\) are integers. \includegraphics[max width=\textwidth, alt={}, center]{1e2fdd33-afa4-486f-a9e2-1d425ed14eee-14_2492_1721_217_150}
AQA Further Paper 3 Statistics 2024 June Q4
6 marks Moderate -0.3
4
8
16
256 2 The random variable \(T\) has an exponential distribution with mean 2 Find \(\mathrm { P } ( T \leq 1.4 )\) Circle your answer. \(\mathrm { e } ^ { - 2.8 }\) \(\mathrm { e } ^ { - 0.7 }\) \(1 - e ^ { - 0.7 }\) \(1 - \mathrm { e } ^ { - 2.8 }\) The continuous random variable \(Y\) has cumulative distribution function $$\mathrm { F } ( y ) = \left\{ \begin{array} { l r } 0 & y < 2 \\ - \frac { 1 } { 9 } y ^ { 2 } + \frac { 10 } { 9 } y - \frac { 16 } { 9 } & 2 \leq y < 5 \\ 1 & y \geq 5 \end{array} \right.$$ Find the median of \(Y\) Circle your answer. 2 \(\frac { 10 - 3 \sqrt { 2 } } { 2 }\) \(\frac { 7 } { 2 }\) \(\frac { 10 + 3 \sqrt { 2 } } { 2 }\) Turn over for the next question 4 Research has shown that the mean number of volcanic eruptions on Earth each day is 20 Sandra records 162 volcanic eruptions during a period of one week. Sandra claims that there has been an increase in the mean number of volcanic eruptions per week. Test Sandra's claim at the \(5 \%\) level of significance.
AQA Further Paper 3 Statistics 2024 June Q8
5 marks Moderate -0.3
8
16
256 2 The random variable \(T\) has an exponential distribution with mean 2 Find \(\mathrm { P } ( T \leq 1.4 )\) Circle your answer. \(\mathrm { e } ^ { - 2.8 }\) \(\mathrm { e } ^ { - 0.7 }\) \(1 - e ^ { - 0.7 }\) \(1 - \mathrm { e } ^ { - 2.8 }\) The continuous random variable \(Y\) has cumulative distribution function $$\mathrm { F } ( y ) = \left\{ \begin{array} { l r } 0 & y < 2 \\ - \frac { 1 } { 9 } y ^ { 2 } + \frac { 10 } { 9 } y - \frac { 16 } { 9 } & 2 \leq y < 5 \\ 1 & y \geq 5 \end{array} \right.$$ Find the median of \(Y\) Circle your answer. 2 \(\frac { 10 - 3 \sqrt { 2 } } { 2 }\) \(\frac { 7 } { 2 }\) \(\frac { 10 + 3 \sqrt { 2 } } { 2 }\) Turn over for the next question 4 Research has shown that the mean number of volcanic eruptions on Earth each day is 20 Sandra records 162 volcanic eruptions during a period of one week. Sandra claims that there has been an increase in the mean number of volcanic eruptions per week. Test Sandra's claim at the \(5 \%\) level of significance.
5 The continuous random variable \(X\) has probability density function $$f ( x ) = \begin{cases} \frac { 1 } { 6 } e ^ { \frac { x } { 3 } } & 0 \leq x \leq \ln 27 \\ 0 & \text { otherwise } \end{cases}$$ Show that the mean of \(X\) is \(\frac { 3 } { 2 } ( \ln 27 - 2 )\) 6 Over time it has been accepted that the mean retirement age for professional baseball players is 29.5 years old. Imran claims that the mean retirement age is no longer 29.5 years old.
He takes a random sample of 5 recently retired professional baseball players and records their retirement ages, \(x\). The results are $$\sum x = 152.1 \quad \text { and } \quad \sum ( x - \bar { x } ) ^ { 2 } = 7.81$$ 6
  1. State an assumption that you should make about the distribution of the retirement ages to investigate Imran's claim. 6
  2. Investigate Imran's claim, using the 10\% level of significance.
AQA Further Paper 3 Statistics 2024 June Q16
Moderate -0.8
16
256 2 The random variable \(T\) has an exponential distribution with mean 2 Find \(\mathrm { P } ( T \leq 1.4 )\) Circle your answer. \(\mathrm { e } ^ { - 2.8 }\) \(\mathrm { e } ^ { - 0.7 }\) \(1 - e ^ { - 0.7 }\) \(1 - \mathrm { e } ^ { - 2.8 }\) The continuous random variable \(Y\) has cumulative distribution function $$\mathrm { F } ( y ) = \left\{ \begin{array} { l r } 0 & y < 2 \\ - \frac { 1 } { 9 } y ^ { 2 } + \frac { 10 } { 9 } y - \frac { 16 } { 9 } & 2 \leq y < 5 \\ 1 & y \geq 5 \end{array} \right.$$ Find the median of \(Y\) Circle your answer. 2 \(\frac { 10 - 3 \sqrt { 2 } } { 2 }\) \(\frac { 7 } { 2 }\) \(\frac { 10 + 3 \sqrt { 2 } } { 2 }\) Turn over for the next question 4 Research has shown that the mean number of volcanic eruptions on Earth each day is 20 Sandra records 162 volcanic eruptions during a period of one week. Sandra claims that there has been an increase in the mean number of volcanic eruptions per week. Test Sandra's claim at the \(5 \%\) level of significance.
5 The continuous random variable \(X\) has probability density function $$f ( x ) = \begin{cases} \frac { 1 } { 6 } e ^ { \frac { x } { 3 } } & 0 \leq x \leq \ln 27 \\ 0 & \text { otherwise } \end{cases}$$ Show that the mean of \(X\) is \(\frac { 3 } { 2 } ( \ln 27 - 2 )\) 6 Over time it has been accepted that the mean retirement age for professional baseball players is 29.5 years old. Imran claims that the mean retirement age is no longer 29.5 years old.
He takes a random sample of 5 recently retired professional baseball players and records their retirement ages, \(x\). The results are $$\sum x = 152.1 \quad \text { and } \quad \sum ( x - \bar { x } ) ^ { 2 } = 7.81$$ 6
  1. State an assumption that you should make about the distribution of the retirement ages to investigate Imran's claim. 6
  2. Investigate Imran's claim, using the 10\% level of significance.
OCR MEI Further Statistics Major Specimen Q2
12 marks Standard +0.3
2 The continuous random variable \(X\) takes values in the interval \(- 1 \leq x \leq 1\) and has probability density function $$f ( x ) = \left\{ \begin{array} { l r } a & - 1 \leq x < 0 \\ a + x ^ { 2 } & 0 \leq x \leq 1 \end{array} \right.$$ where \(a\) is a constant.
  1. (A) Sketch the probability density function.
    (B) Show that \(a = \frac { 1 } { 3 }\).
  2. Find
    (A) \(\mathrm { P } \left( X < \frac { 1 } { 2 } \right)\),
    (B) the mean of \(X\).
  3. Show that the median of \(X\) satisfies the equation \(2 m ^ { 3 } + 2 m - 1 = 0\).
OCR Further Statistics 2021 June Q4
15 marks Standard +0.8
4 The continuous random variable \(X\) has probability density function $$\mathrm { f } ( x ) = \begin{cases} \frac { k } { x ^ { n } } & x \geqslant 1 \\ 0 & \text { otherwise } \end{cases}$$ where \(n\) and \(k\) are constants and \(n\) is an integer greater than 1 .
  1. Find \(k\) in terms of \(n\).
    1. When \(n = 4\), find the cumulative distribution function of \(X\).
    2. Hence determine \(\mathrm { P } ( X > 7 \mid X > 5 )\) when \(n = 4\).
  2. Determine the values of \(n\) for which \(\operatorname { Var } ( X )\) is not defined.
Pre-U Pre-U 9795/2 2010 June Q7
8 marks Standard +0.3
7 The number of goals scored by a hockey team in an interval of time of length \(t\) minutes follows a Poisson distribution with mean \(\frac { 1 } { 24 } t\). The random variable \(T\) is defined as the length of time, in minutes, between successive goals.
  1. (a) Show that \(\mathrm { P } ( T < t ) = 1 - \mathrm { e } ^ { - \frac { 1 } { 24 } t }\) for \(t \geqslant 0\).
    (b) Hence find the probability density function of \(T\).
  2. Find the exact value of the interquartile range of \(T\).
Pre-U Pre-U 9795/2 2013 June Q6
14 marks Challenging +1.2
6 A rectangle of area \(Y \mathrm {~m} ^ { 2 }\) has a perimeter of 16 m and a side of length \(X \mathrm {~m}\), where \(X\) is a random variable with probability density function, f, given by $$f ( x ) = \begin{cases} \frac { 1 } { 2 } & 0 \leqslant x \leqslant 2 \\ 0 & \text { otherwise } \end{cases}$$
  1. Obtain the cumulative distribution function, F , of \(X\).
  2. Show that $$16 - Y = ( 4 - X ) ^ { 2 }$$ and deduce that the probability density function of the random variable \(Y\) is $$g ( y ) = \begin{cases} \frac { 1 } { 4 \sqrt { 16 - y } } & 0 \leqslant y \leqslant 12 \\ 0 & \text { otherwise } \end{cases}$$
  3. Find the median of \(Y\).
  4. Find \(\mathrm { E } ( Y )\).
Pre-U Pre-U 9795/2 2015 June Q6
18 marks Challenging +1.8
6 The object distance, \(U \mathrm {~cm}\), and the image distance, \(V \mathrm {~cm}\), for a convex lens of focal length 40 cm are related by the lens law $$\frac { 1 } { U } + \frac { 1 } { V } = \frac { 1 } { 40 } .$$ The random variable \(U\) is uniformly distributed over the interval \(80 \leqslant u \leqslant 120\).
  1. Show that the probability density function of \(V\) is given by $$f ( v ) = \begin{cases} \frac { 40 } { ( v - 40 ) ^ { 2 } } & 60 \leqslant v \leqslant 80 \\ 0 & \text { otherwise } \end{cases}$$
  2. Find
    1. the median value of \(V\),
    2. the expected value of \(V\).
Pre-U Pre-U 9795/2 2016 Specimen Q6
12 marks Standard +0.8
6 The lengths of time, in years, that sales representatives for a certain company keep their company cars may be modelled by the distribution with probability density function \(\mathrm { f } ( x )\), where $$f ( x ) = \left\{ \begin{array} { c c } \frac { 4 } { 27 } x ^ { 2 } ( 3 - x ) & 0 \leqslant x \leqslant 3 \\ 0 & \text { otherwise } \end{array} \right.$$
  1. Draw a sketch of this probability density function.
  2. Calculate the mean and the mode of \(X\).
  3. Comment briefly on the values obtained in part (ii) in relation to the sketch in part (i).
  4. Show that the lower quartile \(\mathrm { Q } _ { 1 }\) of \(X\) satisfies the equation \(\mathrm { Q } _ { 1 } { } ^ { 4 } - 4 \mathrm { Q } _ { 1 } { } ^ { 3 } + 6.75 = 0\), and use an appropriate numerical method to find the value of \(\mathrm { Q } _ { 1 }\) correct to 2 decimal places, showing full details of your method.
Pre-U Pre-U 9795/2 2017 June Q4
14 marks Standard +0.3
4 A continuous random variable \(X\) has probability density function $$\mathrm { f } ( x ) = \begin{cases} a & - 1 \leqslant x < 0 \\ a \left( 1 - x ^ { 2 } \right) & 0 \leqslant x \leqslant 1 \\ 0 & \text { otherwise } \end{cases}$$ where \(a\) is a constant.
  1. Find the value of \(a\).
  2. Find the cumulative distribution function of \(X\).
  3. Determine whether the upper quartile is greater than or less than 0.25 .
Pre-U Pre-U 9795/2 2019 Specimen Q6
2 marks Standard +0.8
6 The lengths of time, in years, that sales representatives for a certain company keep their company cars may be modelled by the distribution with probability density function \(\mathrm { f } ( x )\), where $$f ( x ) = \left\{ \begin{array} { c c } \frac { 4 } { 27 } x ^ { 2 } ( 3 - x ) & 0 \leqslant x \leqslant 3 , \\ 0 & \text { otherwise } . \end{array} \right.$$
  1. Draw a sketch of this probability density function.
  2. Calculate the mean and the mode of \(X\).
  3. Comment briefly on the values obtained in part (b) in relation to the sketch in part (a).
  4. Show that the lower quartile \(\mathrm { Q } _ { 1 }\) of \(X\) satisfies the equation \(\mathrm { Q } _ { 1 } { } ^ { 4 } - 4 \mathrm { Q } _ { 1 } { } ^ { 3 } + 6.75 = 0\), and use an appropriate numerical method to find the value of \(\mathrm { Q } _ { 1 }\) correct to 2 decimal places, showing full details of your method.
WJEC Unit 4 2023 June Q3
Standard +0.2
The continuous random variable \(X\) is uniformly distributed over the interval \([ 1 , d ]\). a) The 90 th percentile of \(X\) is 19 . Find the value of \(d\).
b) Calculate the mean and standard deviation of \(X\).
\(\mathbf { 0 }\)\(\mathbf { 4 } \quad\) A bakery produces large loaves with masses, in grams, that are normally distributed
with mean \(\mu\) and variance \(\sigma ^ { 2 }\). It is found that \(11 \%\) of the large loaves weigh more than 805 g and that \(20 \%\) of the large loaves weigh less than 795 g .
a) Find the values of \(\mu\) and \(\sigma\). The bakery also produces small loaves with masses, in grams, that are normally distributed with mean 400 and standard deviation 9 . Following a change of management at the bakery, a customer suspects that the mean mass of the small loaves has decreased. The customer weighs the next 15 small loaves that he purchases and calculates their mean mass to be 397 g .
b) Perform a hypothesis test at the \(5 \%\) significance level to investigate the customer's suspicion, assuming the standard deviation, in grams, is still 9.
c) State another assumption you have made in part (b). 5 A medical researcher is investigating possible links between diet and a particular disease. She selects a random sample of 22 countries and records the average daily calorie intake per capita from sugar and the percentage of the population who suffer from this disease. \begin{figure}[h]
\captionsetup{labelformat=empty} \caption{Sugar consumption and rate of disease} \includegraphics[alt={},max width=\textwidth]{9c111615-42d5-4804-8eb3-c20fe8d9faee-05_654_1264_591_461}
\end{figure} There are 22 data points and the product moment correlation coefficient is \(0 \cdot 893\).
a) Stating your hypotheses clearly, show that these data could be used to suggest that there is a link between the disease and sugar consumption. The medical researcher realises that her data is from the year 2000. She repeats her investigation with a random sample of 13 countries using new data from the year 2020. She produces the following graph. \begin{figure}[h]
\captionsetup{labelformat=empty} \caption{Sugar consumption and rate of disease} \includegraphics[alt={},max width=\textwidth]{9c111615-42d5-4804-8eb3-c20fe8d9faee-05_700_1273_1763_461}
\end{figure} b) How should the researcher interpret the new data in the light of the data from 2000? \section*{Section B: Differential Equations and Mechanics}
06
A particle \(P\) moves on a horizontal plane, where \(\mathbf { i }\) and \(\mathbf { j }\) are unit vectors in directions east and north respectively. At time \(t\) seconds, the position vector of \(P\) is given by \(\mathbf { r }\) metres, where $$\mathbf { r } = \left( t ^ { 3 } - 7 t ^ { 2 } \right) \mathbf { i } + \left( 2 t ^ { 2 } - 15 t + 11 \right) \mathbf { j }$$ a) i) Find an expression for the velocity vector of \(P\) at time \(t \mathrm {~s}\).
ii) Determine the value of \(t\) when \(P\) is moving north-east and hence write down the velocity of \(P\) at this value of \(t\).
b) Find the acceleration vector of \(P\) when \(t = 7\).
\(\mathbf { 0 }\)\(\mathbf { 7 } \quad\) A rod \(A B\), of mass 20 kg and length 3.2 m , is resting horizontally in equilibrium on two
smooth supports at points \(X\) and \(Y\), where \(A X = 0.4 \mathrm {~m}\) and \(A Y = 2.4 \mathrm {~m}\). A particle of mass 8 kg is attached to the rod at a point \(C\), where \(B C = 0.2 \mathrm {~m}\). The reaction of the support at \(Y\) is four times the reaction of the support at \(X\). You may not assume that the rod \(A B\) is uniform.
a) i) Find the magnitude of each of the reaction forces exerted on the rod at \(X\) and \(Y\).
ii) Show that the weight of the rod acts at the midpoint of \(A B\).
b) Is it now possible to determine whether the rod is uniform or non-uniform? Give a reason for your answer. A boy kicks a ball from a point \(O\) on horizontal ground towards a vertical wall \(A B\). The initial speed of the ball is \(23 \mathrm {~ms} ^ { - 1 }\) in a direction that is \(18 ^ { \circ }\) above the horizontal. The diagram below shows a window \(C D\) in the wall \(A B\), such that \(B D = 1.1 \mathrm {~m}\) and \(B C = 2 \cdot 2 \mathrm {~m}\). The horizontal distance from \(O\) to \(B\) is 8 m . \includegraphics[max width=\textwidth, alt={}, center]{9c111615-42d5-4804-8eb3-c20fe8d9faee-07_567_1540_605_274} You may assume that the window will break if the ball strikes it with a speed of at least \(21 \mathrm {~ms} ^ { - 1 }\).
a) Show that the ball strikes the window and determine whether or not the window breaks.
b) Give one reason why your answer to part (a) may be unreliable. The diagram below shows a wooden crate of mass 35 kg being pushed on a rough horizontal floor, by a force of magnitude 380 N inclined at an angle of \(30 ^ { \circ }\) below the horizontal. The crate, which may be modelled as a particle, is moving at a constant speed. \includegraphics[max width=\textwidth, alt={}, center]{9c111615-42d5-4804-8eb3-c20fe8d9faee-08_394_665_573_701}
a) The coefficient of friction between the crate and the floor is \(\mu\). Show that $$\mu = \frac { 190 \sqrt { 3 } } { 533 } .$$ Suppose instead that the crate is pulled with the same force of 380 N inclined at an angle of \(30 ^ { \circ }\) above the horizontal, as shown in the diagram below. \includegraphics[max width=\textwidth, alt={}, center]{9c111615-42d5-4804-8eb3-c20fe8d9faee-08_392_663_1425_701}
b) Without carrying out any further calculations, explain why the crate will no longer move at a constant speed.
CAIE FP2 2012 June Q8
9 marks Standard +0.3
The number of flaws in a randomly chosen 100 metre length of ribbon is modelled by a Poisson distribution with mean 1.6. The random variable \(X\) metres is the distance between two successive flaws. Show that the distribution function of \(X\) is given by $$\text{F}(x) = \begin{cases} 1 - e^{-0.016x} & x \geq 0, \\ 0 & x < 0, \end{cases}$$ and deduce that \(X\) has a negative exponential distribution, stating its mean. [4] Find
  1. the median distance between two successive flaws, [3]
  2. the probability that there is a distance of at least 50 metres between two successive flaws. [2]
CAIE FP2 2012 June Q8
9 marks Standard +0.3
The number of flaws in a randomly chosen 100 metre length of ribbon is modelled by a Poisson distribution with mean 1.6. The random variable \(X\) metres is the distance between two successive flaws. Show that the distribution function of \(X\) is given by $$\text{F}(x) = \begin{cases} 1 - e^{-0.016x} & x \geqslant 0, \\ 0 & x < 0, \end{cases}$$ and deduce that \(X\) has a negative exponential distribution, stating its mean. [4] Find
  1. the median distance between two successive flaws, [3]
  2. the probability that there is a distance of at least 50 metres between two successive flaws. [2]
CAIE FP2 2014 November Q7
6 marks Standard +0.3
The time, \(T\) seconds, between successive cars passing a particular checkpoint on a wide road has probability density function f given by $$f(t) = \begin{cases} \frac{1}{100}e^{-0.01t} & t \geq 0, \\ 0 & \text{otherwise.} \end{cases}$$
  1. State the expected value of \(T\). [1]
  2. Find the median value of \(T\). [3]
Sally wishes to cross the road at this checkpoint and she needs 20 seconds to complete the crossing. She decides to start out immediately after a car passes. Find the probability that she will complete the crossing before the next car passes. [2]
CAIE FP2 2015 November Q7
9 marks Standard +0.8
The continuous random variable \(X\) has probability density function given by $$f(x) = \begin{cases} \frac{1}{2t}x^2 & 1 \leq x \leq 4, \\ 0 & \text{otherwise}. \end{cases}$$ The random variable \(Y\) is defined by \(Y = X^2\). Show that \(Y\) has probability density function given by $$g(y) = \begin{cases} \left(\frac{1}{2t}\right)y^{\frac{1}{2}} & 1 \leq y \leq 16, \\ 0 & \text{otherwise}. \end{cases}$$ [5] Find
  1. the median value of \(Y\), [2]
  2. the expected value of \(Y\). [2]