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2022 Paper 2 Q11
D: 1500.0 B: 1500.0
discrete probability distributions expected value optimisation binomial distribution calculus hypothesis testing conditional probability

A batch of \(N\) USB sticks is to be used on a network. Each stick has the same unknown probability \(p\) of being infected with a virus. Each stick is infected, or not, independently of the others. The network manager decides on an integer value of \(T\) with \(0 \leqslant T < N\). If \(T = 0\) no testing takes place and the \(N\) sticks are used on the network, but if \(T > 0\), the batch is subject to the following procedure.

  • Each of \(T\) sticks, chosen at random from the batch, undergoes a test during which it is destroyed.
  • If any of these \(T\) sticks is infected, all the remaining \(N - T\) sticks are destroyed.
  • If none of the \(T\) sticks is infected, the remaining \(N - T\) sticks are used on the network.
If any stick used on the network is infected, the network has to be disinfected at a cost of \(\pounds D\), where \(D > 0\). If no stick used on the network is infected, there is a gain of \(\pounds 1\) for each of the \(N - T\) sticks. There is no cost to testing or destroying a stick.
  1. Find an expression in terms of \(N\), \(T\), \(D\) and \(q\), where \(q = 1 - p\), for the expected net loss.
  2. Let \(\alpha = \dfrac{DT}{N(N - T + D)}\). Show that \(0 \leqslant \alpha < 1\). Show that, for fixed values of \(N\), \(D\) and \(T\), the greatest value of the expected net loss occurs when \(q\) satisfies the equation \(q^{N-T} = \alpha\). Show further that this greatest value is \(\pounds\dfrac{D(N-T)\,\alpha^k}{N}\), where \(k = \dfrac{T}{N-T}\).
  3. For fixed values of \(N\) and \(D\), show that there is some \(\beta > 0\) so that for all \(p < \beta\), the expression for the expected loss found in part (i) is an increasing function of \(T\). Deduce that, for small enough values of \(p\), testing no sticks minimises the expected net loss.

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2015 Paper 1 Q7
D: 1500.0 B: 1500.0
optimisation cubic polynomial greatest value on interval piecewise function stationary points calculus parameter ranges

Let \[ \f(x) = 3ax^2 - 6x^3\, \] and, for each real number \(a\), let \({\rm M}(a)\) be the greatest value of \(\f(x)\) in the interval \(-\frac13 \le x \le 1\). Determine \({\rm M} (a)\) for \(a\ge0\). [The formula for \({\rm M} (a)\) is different in different ranges of \(a\); you will need to identify three ranges.]

Solution: \(f'(x) = 6ax-18x^2\), therefore \(f\) has turning points at \(0\) and \(\frac{a}3\) (ie decreasing for \(x \leq 0\) and \(x \geq \frac{a}{3}\) and increasing otherwise). Therefore possible maxima are \(f(-\tfrac13), f(\frac{a}{3}), f(1)\) where we consider \(\frac{a}{3}\) if \(a \leq 3\) and \(1\) otherwise. \(f(-\frac13) = \frac{a}{3} + \frac{2}{9} = \frac{3a+2}{9}\) \(f(\frac{a}{3}) = \frac{a^3}{3} - \frac{2a^3}{9} = \frac{a^3}{9}\) \(f(1) = 3(a-2)\) Comparing \(\frac{a^3}{9}\) to \(\frac{3a+2}{9}\) we have a double root at \(a = -1\) and a single root at \(a = 2\), therefore \(\frac{a^3}9\) is larger if \(a \geq 2\) Comparing \(3(a-2)\) to \(\frac{3a+2}9\) we have a cross-over at \(a = \frac{7}3\). Therefore we have: \begin{align*} M(a) &= \begin{cases} \frac{3a+2}{9} & 0 \leq a \leq 2 \\ \frac{a^3}{9} & 2 \leq a \leq 3 \\ 3(a-2) & 3 \leq a \end{cases} \end{align*}

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2015 Paper 2 Q1
D: 1600.0 B: 1516.0
Taylor series logarithm inequality summation harmonic series calculus monotonic function series bounds

  1. By use of calculus, show that \(x- \ln(1+x)\) is positive for all positive \(x\). Use this result to show that \[ \sum_{k=1}^n \frac 1 k > \ln (n+1) \,. \]
  2. By considering \( x+\ln (1-x)\), show that \[ \sum_{k=1}^\infty \frac 1 {k^2} <1+ \ln 2 \,. \]

Solution:

  1. Consider \(f(x) = x - \ln (1+ x)\), then \(f'(x) = 1 - \frac{1}{1+x} = \frac{x}{1+x} > 0\) if \(x >0\). Therefore \(f(x)\) is strictly increasing on the positive reals. Since \(f(0) = 0\) we must have \(f(x) > 0\) for all positive \(x\), ie \(x - \ln(1+x)\) is positive for all positive \(x\). \begin{align*} \sum_{k=1}^n \frac1k &\underbrace{>}_{x > \ln(1+x)} \sum_{k=1}^n \ln \left (1 + \frac1k \right ) \\ &= \sum_{k=1}^n \ln \left ( \frac{k+1}{k} \right ) \\ &= \sum_{k=1}^n \left ( \ln (k+1) - \ln (k) \right) \\ &= \ln (n+1) - \ln 1 \\ &= \ln (n+1) \end{align*}
  2. Let \(g(x) = x + \ln (1-x)\) ,then \(g'(x) = 1 - \frac{1}{1-x} = \frac{-x}{1-x} < 0\) if \(0 < x < 1\) and \(g(0) = 0\). Therefore \(g(x)\) is decreasing and hence negative on \(0 < x < 1\), in particular \(x < -\ln(1-x) \) \begin{align*} \sum_{k=2}^n \frac1{k^2} &\underbrace{<}_{x < -\ln(1+x)} \sum_{k=2}^n - \ln \left (1-\frac1{k^2} \right) \\ &= -\sum_{k=2}^n \ln \left ( \frac{k^2-1}{k^2}\right) \\ &= \sum_{k=2}^n \l 2 \ln k - \ln(k-1) - \ln(k+1) \r \\ &= \ln n - \ln(n+1) - \ln 0+\ln 2 \\ &= \ln 2 + \ln \frac{n}{n+1} \end{align*} as \(n \to \infty\) we must have \(\displaystyle \sum_{k=2}^{\infty} \frac1{k^2} < \ln 2\) ie \[ \sum_{k=1}^\infty \frac 1 {k^2} <1+ \ln 2\]

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1998 Paper 1 Q4
D: 1500.0 B: 1533.8
optimisation circle rectangle inequality calculus maximisation power sums geometric proof

Prove that the rectangle of greatest perimeter which can be inscribed in a given circle is a square. The result changes if, instead of maximising the sum of lengths of sides of the rectangle, we seek to maximise the sum of \(n\)th powers of the lengths of those sides for \(n\geqslant 2\). What happens if \(n=2\)? What happens if \(n=3\)? Justify your answers.

Solution: We can always rotate the circle so that sides are parallel to the \(x\) and \(y\) axes. Therefore if one corner is \((a,b)\) the other coordinates are \((-a,b), (a,-b), (-a,-b)\) and the perimeter will be \(4(a+b)\). Therefore we wish to maximise \(4(a+b)\) subject to \(a^2+b^2 = \text{some constant}\). Notice that \(\frac{a+b}{2} \leq \sqrt{\frac{a^2+b^2}{2}}\) with equality when \(a = b\), therefore the maximum is a square. If \(n = 2\) then we are looking at \(2((2a)^2+(2b)^2) = 8(a^2+b^2)\) which is constant for all rectangles. If \(n=3\) we are maximising \(16(a^3+b^3) = 16(a^3+(c^2-a^2)^{3/2})\) which is maximised when \(a = 0, c\)

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1998 Paper 1 Q11
D: 1500.0 B: 1502.5
pulley systems Newton's second law constant acceleration optimisation calculus connected particles vertical motion ore mine

Hank's Gold Mine has a very long vertical shaft of height \(l\). A light chain of length \(l\) passes over a small smooth light fixed pulley at the top of the shaft. To one end of the chain is attached a bucket \(A\) of negligible mass and to the other a bucket \(B\) of mass \(m\). The system is used to raise ore from the mine as follows. When bucket \(A\) is at the top it is filled with mass \(2m\) of water and bucket \(B\) is filled with mass \(\lambda m\) of ore, where \(0<\lambda<1\). The buckets are then released, so that bucket \(A\) descends and bucket \(B\) ascends. When bucket \(B\) reaches the top both buckets are emptied and released, so that bucket \(B\) descends and bucket \(A\) ascends. The time to fill and empty the buckets is negligible. Find the time taken from the moment bucket \(A\) is released at the top until the first time it reaches the top again. This process goes on for a very long time. Show that, if the greatest amount of ore is to be raised in that time, then \(\lambda\) must satisfy the condition \(\mathrm{f}'(\lambda)=0\) where \[\mathrm{f}(\lambda)=\frac{\lambda(1-\lambda)^{1/2}} {(1-\lambda)^{1/2}+(3+\lambda)^{1/2}}.\]

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1998 Paper 2 Q11
D: 1600.0 B: 1546.5
projectiles trigonometry constant rate of change tan theta line of sight cricket relative motion calculus

A fielder, who is perfectly placed to catch a ball struck by the batsman in a game of cricket, watches the ball in flight. Assuming that the ball is struck at the fielder's eye level and is caught just in front of her eye, show that \(\frac{ {\rm d}}{{\rm d t}} (\tan\theta ) \) is constant, where \(\theta\) is the angle between the horizontal and the fielder's line of sight. In order to catch the next ball, which is also struck towards her but at a different velocity, the fielder runs at constant speed \(v\) towards the batsman. Assuming that the ground is horizontal, show that the fielder should choose \(v\) so that \(\frac{ {\rm d}}{{\rm d t}} (\tan\theta ) \) remains constant.

Solution: Set up a coordinate frame such that the position of the catch is the origin and the time of the catch is \(t = 0\) . We must have then that the trajectory of the ball is \(\mathbf{s} =\mathbf{u} t + \frac12 \mathbf{g} t^2 = \binom{u_x t}{u_y t - \frac12 gt^2}\). We must then have: \begin{align*} && \tan \theta &= \frac{u_y t - \frac12 gt^2}{u_x t} \\ &&&= \frac{u_y}{u_x} - \frac{g}{2u_x} t \\ \Rightarrow && \frac{\d}{\d \theta} \left ( \tan \theta \right) &= 0 - \frac{g}{2 u_x} \end{align*} which is clearly constant. Set coordinates so \(y\)-axis starts from eye-level and \(t = 0\) the first time the ball reaches that level. (Or move the trajectory backwards if that's not the case). Then the ball has trajectory \(\binom{u_xt}{u_yt - \frac12 gt^2}\). The ball reaches eye level a second time when \(t = \frac{2u_y}{g}\), ie at a point \(\frac{2u_xu_y}{g}\). The fielder therefore needs to have position \(f + (u_x-\frac{g}{2u_y}f)t\) at all times. Therefore \begin{align*} && \tan \theta &= \frac{u_y t - \frac12 gt^2}{f + (u_x-\frac{g}{2u_y}f)t - u_x t} \\ &&&= \frac{u_y t - \frac12 gt^2}{f(1-\frac{g}{2u_y}t)} \\ &&&= \frac{u_yt ( 1- \frac{g}{2u_y}t)}{f( 1- \frac{g}{2u_y}t)} \\ &&&= u_y t \\ \Rightarrow && \frac{\d}{\d \theta} \left ( \tan \theta \right) &= u_y \end{align*} Ie \( \frac{\d}{\d \theta} \left ( \tan \theta \right) \) is constant as required.

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1995 Paper 2 Q5
D: 1600.0 B: 1545.6
coordinate geometry circle optimisation trigonometry calculus speed-distance-time circumference chord length

The famous film star Birkhoff Maclane is sunning herself by the side of her enormous circular swimming pool (with centre \(O\)) at a point \(A\) on its circumference. She wants a drink from a small jug of iced tea placed at the diametrically opposite point \(B\). She has three choices:

  1. to swim directly to \(B\).
  2. to choose \(\theta\) with \(0<\theta<\pi,\) to run round the pool to a point \(X\) with \(\angle AOX=\theta\) and then to swim directly from \(X\) to \(B\).
  3. to run round the pool from \(A\) to \(B\).
She can run \(k\) times as fast as she can swim and she wishes to reach her tea as fast as possible. Explain, with reasons, which of (i), (ii) and (iii) she should choose for each value of \(k\). Is there one choice from (i), (ii) and (iii) she will never take whatever the value of \(k\)?

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