5.03b Solve problems: using pdf

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Pre-U Pre-U 9795/2 2016 June Q7
10 marks Challenging +1.8
7 A continuous random variable \(X\) has probability density function $$f ( x ) = \begin{cases} \frac { 3 x ^ { 2 } } { k ^ { 3 } } & 0 \leqslant x \leqslant k \\ 0 & \text { otherwise } \end{cases}$$ where \(k\) is a parameter.
  1. Find \(\mathrm { E } ( X )\). Hence show that \(\frac { 4 } { 3 } X\) is an unbiased estimator of \(k\). Three independent observations of \(X\) are denoted by \(X _ { 1 } , X _ { 2 }\) and \(X _ { 3 }\), and the largest value of \(X _ { 1 } , X _ { 2 }\) and \(X _ { 3 }\) is denoted by \(M\).
  2. Write down an expression for \(\mathrm { P } ( M \leqslant x )\), and hence show that the probability density function of \(M\) is $$f _ { M } ( x ) = \begin{cases} \frac { 9 x ^ { 8 } } { k ^ { 9 } } & 0 \leqslant x \leqslant k \\ 0 & \text { otherwise } . \end{cases}$$
  3. Find \(\mathrm { E } ( M )\) and use your answer to construct an unbiased estimator of \(k\) based on \(M\).
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 2018 June Q4
Challenging +1.2
4 The continuous random variable \(X\) has cumulative distribution function given by $$\mathrm { F } ( x ) = \begin{cases} 0 & x < 0 \\ \frac { 1 } { 8 } x ^ { 3 } & 0 \leqslant x \leqslant 2 \\ 1 & x > 2 \end{cases}$$
  1. Find \(\mathrm { E } ( X )\).
  2. Find the probability density function of \(Y\), where \(Y = \frac { 1 } { X ^ { 2 } }\).
Pre-U Pre-U 9795/2 2019 Specimen Q5
3 marks Standard +0.3
5 The random variable \(X\) has probability density function \(\mathrm { f } ( \mathrm { x } )\), where $$\mathrm { f } ( x ) = \begin{cases} k \mathrm { e } ^ { - k x } & x \geqslant 0 \\ 0 & x < 0 \end{cases}$$ and \(k\) is a positive constant.
  1. Show that the moment generating function of \(X\) is \(\mathrm { M } _ { X } ( t ) = k ( k - t ) ^ { - 1 } , t < k\).
  2. Use the moment generating function to find \(\mathrm { E } ( X )\) and \(\operatorname { Var } ( X )\).
  3. Show that the moment generating function of \(- X\) is \(k ( k + t ) ^ { - 1 }\).
  4. \(X _ { 1 }\) and \(X _ { 2 }\) are two independent observations of \(X\). Use the moment generating function of \(X _ { 1 } - X _ { 2 }\) to find the value of \(\mathrm { E } \left[ \left( X _ { 1 } - X _ { 2 } \right) ^ { 2 } \right]\).
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.
Pre-U Pre-U 9795/2 2020 Specimen Q6
2 marks Standard +0.3
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.
Pre-U Pre-U 9795/2 Specimen Q9
4 marks Standard +0.8
9 The service time, \(X\) minutes, for each customer in a post office is modelled by the probability density function given by $$\mathrm { f } ( x ) = \begin{cases} 0.2 \mathrm { e } ^ { - 0.2 x } & x > 0 , \\ 0 & \text { otherwise } . \end{cases}$$ Two customers begin to be served independently at the same instant. The larger of the two service times is \(T\) minutes.
  1. By considering the probability that both customers have been served in less than \(t\) minutes, show that the cumulative distribution function of \(T\) is given by $$\mathrm { G } ( t ) = \begin{cases} 1 - 2 \mathrm { e } ^ { - 0.2 t } + \mathrm { e } ^ { - 0.4 t } & t > 0 \\ 0 & \text { otherwise } \end{cases}$$
  2. Find the probability that both customers are served within 10 minutes.
  3. Find the value of the interquartile range of \(T\).
Pre-U Pre-U 9795/2 Specimen Q11
11 marks Standard +0.3
11 The time, \(T\) years, before a particular type of washing machine breaks down may be taken to have probability density function f given by $$\mathrm { f } ( t ) = \begin{cases} a t \mathrm { e } ^ { - b t } & t > 0 \\ 0 & \text { otherwise } \end{cases}$$ where \(a\) and \(b\) are positive constants. It may be assumed that, if \(n\) is a positive integer, $$\int _ { 0 } ^ { \infty } t ^ { n } \mathrm { e } ^ { - b t } \mathrm {~d} t = \frac { n ! } { b ^ { n + 1 } }$$
  1. Records show that the mean of \(T\) is 1.5 . Show that \(b = \frac { 4 } { 3 }\) and find the value of \(a\).
  2. Find \(\operatorname { Var } ( T )\).
  3. Calculate \(\mathrm { P } ( T < 1.5 )\). State, giving a reason, whether this value indicates that the median of \(T\) is smaller than the mean of \(T\) or greater than the mean of \(T\).
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 2010 June Q7
7 marks Standard +0.8
The continuous random variable \(X\) has distribution function given by $$\text{F}(x) = \begin{cases} 0 & x < 0, \\ 1 - e^{-\frac{x}{4}} & x \geqslant 0. \end{cases}$$ For a random value of \(X\), find the probability that \(2\) lies between \(X\) and \(4X\). [3] Find also the expected value of the width of the interval \((X, 4X)\). [4]
CAIE FP2 2010 June Q11
28 marks Challenging +1.8
Answer only one of the following two alternatives. **EITHER** \includegraphics{figure_11a} A uniform disc, of mass \(4m\) and radius \(a\), and a uniform ring, of mass \(m\) and radius \(2a\), each have centre \(O\). A wheel is made by fixing three uniform rods, \(OA\), \(OB\) and \(OC\), each of mass \(m\) and length \(2a\), to the disc and the ring, as shown in the diagram. Show that the moment of inertia of the wheel about an axis through \(A\), perpendicular to the plane of the wheel, is \(42ma^2\). [5] The axis through \(A\) is horizontal, and the wheel can rotate freely about this axis. The wheel is released from rest with \(O\) above the level of \(A\) and \(AO\) making an angle of \(30°\) with the horizontal. Find the angular speed of the wheel when \(AO\) is horizontal. [3] When \(AO\) is horizontal the disc becomes detached from the wheel. Find the angle that \(AO\) makes with the horizontal when the wheel first comes to instantaneous rest. [6] **OR** The continuous random variable \(T\) has probability density function given by $$f(t) = \begin{cases} 0 & t < 2, \\ \frac{2}{(t-1)^3} & t \geqslant 2. \end{cases}$$
  1. Find the distribution function of \(T\), and find also P\((T > 5)\). [3]
  2. Consecutive independent observations of \(T\) are made until the first observation that exceeds \(5\) is obtained. The random variable \(N\) is the total number of observations that have been made up to and including the observation exceeding \(5\). Find P\((N > E(N))\). [3]
  3. Find the probability density function of \(Y\), where \(Y = \frac{1}{T-1}\). [8]
CAIE FP2 2017 June Q8
10 marks Standard +0.8
The continuous random variable \(X\) has probability density function f given by $$\text{f}(x) = \begin{cases} \frac{1}{4}(x - 1) & 2 \leqslant x \leqslant 4, \\ 0 & \text{otherwise.} \end{cases}$$
  1. Find the distribution function of \(X\). [3]
The random variable \(Y\) is defined by \(Y = (X - 1)^3\).
  1. Find the probability density function of \(Y\). [4]
  2. Find the median value of \(Y\). [3]
CAIE FP2 2017 June Q8
10 marks Standard +0.3
The continuous random variable \(X\) has probability density function \(f\) given by $$f(x) = \begin{cases} \frac{1}{4}(x - 1) & 2 \leqslant x \leqslant 4, \\ 0 & \text{otherwise}. \end{cases}$$
  1. Find the distribution function of \(X\). [3]
  2. The random variable \(Y\) is defined by \(Y = (X - 1)^3\). Find the probability density function of \(Y\). [4]
  3. Find the median value of \(Y\). [3]
CAIE FP2 2018 November Q7
7 marks Standard +0.3
The random variable \(T\) is the lifetime, in hours, of a particular type of battery. It is given that \(T\) has a negative exponential distribution with mean 500 hours.
  1. Write down the probability density function of \(T\). [1]
  2. Find the probability that a randomly chosen battery of this type has a lifetime of more than 750 hours. [3]
  3. Find the median value of \(T\). [3]
CAIE FP2 2019 November Q7
7 marks Standard +0.3
The time, \(T\) days, before an electrical component develops a fault has distribution function F given by $$\mathrm{F}(t) = \begin{cases} 1 - e^{-at} & t \geqslant 0, \\ 0 & \text{otherwise}, \end{cases}$$ where \(a\) is a positive constant. The mean value of \(T\) is 200.
  1. Write down the value of \(a\). [1]
  2. Find the probability that an electrical component of this type develops a fault in less than 150 days. [2]
A piece of equipment contains \(n\) of these components, which develop faults independently of each other. The probability that, after 150 days, at least one of the \(n\) components has not developed a fault is greater than 0.99.
  1. Find the smallest possible value of \(n\). [4]
CAIE S2 2021 June Q6
6 marks Standard +0.3
The probability density function, f, of a random variable \(X\) is given by $$\text{f}(x) = \begin{cases} k(6x - x^2) & 0 \leq x \leq 6, \\ 0 & \text{otherwise,} \end{cases}$$ where \(k\) is a constant. State the value of \(\text{E}(X)\) and show that \(\text{Var}(X) = \frac{9}{5}\). [6]
CAIE S2 2022 November Q7
8 marks Standard +0.3
\includegraphics{figure_7} The diagram shows the graph of the probability density function, f, of a random variable \(X\) which takes values between \(-3\) and 2 only.
  1. Given that the graph is symmetrical about the line \(x = -0.5\) and that P(\(X < 0\)) = \(p\), find P(\(-1 < X < 0\)) in terms of \(p\). [2]
  2. It is now given that the probability density function shown in the diagram is given by $$\text{f}(x) = \begin{cases} a - b(x^2 + x) & -3 \leq x \leq 2, \\ 0 & \text{otherwise,} \end{cases}$$ where \(a\) and \(b\) are positive constants.
    1. Show that \(30a - 55b = 6\). [3]
    2. By substituting a suitable value of \(x\) into f(\(x\)), find another equation relating \(a\) and \(b\) and hence determine the values of \(a\) and \(b\). [3]
CAIE S2 2023 November Q6
8 marks Standard +0.8
A continuous random variable \(X\) takes values from 0 to 6 only and has a probability distribution that is symmetrical. Two values, \(a\) and \(b\), of \(X\) are such that P\((a < X < b) = p\) and P\((b < X < 3) = \frac{13}{10}p\), where \(p\) is a positive constant.
  1. Show that \(p \leq \frac{5}{23}\). [1]
  2. Find P\((b < X < 6 - a)\) in terms of \(p\). [2]
It is now given that the probability density function of \(X\) is \(f\), where $$f(x) = \begin{cases} \frac{1}{36}(6x - x^2) & 0 \leq x \leq 6, \\ 0 & \text{otherwise}. \end{cases}$$
  1. Given that \(b = 2\) and \(p = \frac{5}{81}\), find the value of \(a\). [5]
CAIE S2 2011 June Q7
9 marks Moderate -0.3
A random variable \(X\) has probability density function given by $$f(x) = \begin{cases} k(1-x) & -1 \leq x \leq 1, \\ 0 & \text{otherwise}, \end{cases}$$ where \(k\) is a constant.
  1. Show that \(k = \frac{1}{2}\). [2]
  2. Find \(\text{P}(X > \frac{1}{2})\). [1]
  3. Find the mean of \(X\). [3]
  4. Find \(a\) such that \(\text{P}(X < a) = \frac{1}{3}\). [3]
Edexcel S2 2016 January Q2
10 marks Moderate -0.3
The continuous random variable \(X\) is uniformly distributed over the interval \([a, b]\) Given that \(\mathrm{P}(3 < X < 5) = \frac{1}{8}\) and \(\mathrm{E}(X) = 4\)
  1. find the value of \(a\) and the value of \(b\) [3]
  2. find the value of the constant, \(c\), such that \(\mathrm{E}(cX - 2) = 0\) [2]
  3. find the exact value of \(\mathrm{E}(X^2)\) [3]
  4. find \(\mathrm{P}(2X - b > a)\) [2]
Edexcel S2 2016 January Q6
15 marks Standard +0.3
A continuous random variable \(X\) has probability density function $$\mathrm{f}(x) = \begin{cases} ax^2 + bx & 1 \leq x \leq 7 \\ 0 & \text{otherwise} \end{cases}$$ where \(a\) and \(b\) are constants.
  1. Show that \(114a + 24b = 1\) [4]
Given that \(a = \frac{1}{90}\)
  1. use algebraic integration to find \(\mathrm{E}(X)\) [4]
  2. find the cumulative distribution function of \(X\), specifying it for all values of \(x\) [3]
  3. find \(\mathrm{P}(X > \mathrm{E}(X))\) [2]
  4. use your answer to part (d) to describe the skewness of the distribution. [2]
Edexcel S2 Q6
14 marks Standard +0.3
The continuous random variable X has cumulative distribution function F(x) given by $$\text{F}(x) = \begin{cases} 0, & x < 1 \\ \frac{1}{2}(-x^3 + 6x^2 - 5), & 1 \leq x \leq 4 \\ 1, & x > 4 \end{cases}$$
  1. Find the probability density function f(x). [3]
  2. Find the mode of X. [2]
  3. Sketch f(x) for all values of x. [3]
  4. Find the mean \(\mu\) of X. [3]
  5. Show that F(\(\mu\)) > 0.5. [1]
  6. Show that the median of X lies between the mode and the mean. [2]
Edexcel S2 Q7
16 marks Standard +0.3
A continuous random variable X has cumulative distribution function F(x) given by $$\text{F}(x) = \begin{cases} 0, & x < 0, \\ kx^2 + 2kx, & 0 \leq x \leq 2, \\ 8k, & x > 2. \end{cases}$$
  1. Show that \(k = \frac{1}{8}\). [1]
  2. Find the median of X. [3]
  3. Find the probability density function f(x). [3]
  4. Sketch f(x) for all values of x. [3]
  5. Write down the mode of X. [1]
  6. Find E(X). [3]
  7. Comment on the skewness of this distribution. [2]
Edexcel S2 Q7
17 marks Standard +0.3
The continuous random variable X has probability density function $$f(x) = \begin{cases} \frac{x}{15}, & 0 \leq x \leq 2, \\ \frac{x}{15}, & \\ \frac{2x}{45}, & 2 < x < 7, \\ \frac{2}{9}, & 7 \leq x \leq 10, \\ 0, & otherwise. \end{cases}$$
  1. Sketch f(x) for all values of x. [3]
  2. Find expressions for the cumulative distribution function, F(x), for 0 ≤ x ≤ 2 and for 7 ≤ x ≤ 10. [8]
  3. Find P(X ≤ 8.2). [2]
  4. Find, to 3 significant figures, E(X). [4]
Edexcel S2 Q4
14 marks Standard +0.3
The continuous random variable X has cumulative distribution function $$\text{F}(x) = \begin{cases} 0, & x < 0, \\ \frac{1}{4}x²(4 - x²), & 0 \leq x \leq 1, \\ 1, & x > 1. \end{cases}$$
  1. Find P(X > 0.7). [2]
  2. Find the probability density function f(x) of X. [2]
  3. Calculate E(X) and show that, to 3 decimal places, Var(X) = 0.057. [6]
One measure of skewness is $$\frac{\text{Mean} - \text{Mode}}{\text{Standard deviation}}$$
  1. Evaluate the skewness of the distribution of X. [4]