Pre-U Pre-U 9795/2 2018 June — Question 6

Exam BoardPre-U
ModulePre-U 9795/2 (Pre-U Further Mathematics Paper 2)
Year2018
SessionJune
TopicCentral limit theorem
TypeEstimator properties and bias
DifficultyChallenging +1.3 This question requires understanding of expectation/variance of discrete uniform distributions, unbiased estimators, and the Central Limit Theorem for approximate distributions. Part (i) involves standard summation formulas (routine for Further Maths). Part (ii) applies CLT straightforwardly. Part (iii) requires algebraic manipulation to compare variances. While multi-step, each component uses standard techniques without requiring novel insight—moderately above average difficulty for Further Maths statistics.
Spec5.05a Sample mean distribution: central limit theorem5.05b Unbiased estimates: of population mean and variance

6 In a certain city there are \(N\) taxis. Each taxi displays a different licensing number which is an integer in the range 1 to \(N\). A visitor to the city attempts to estimate the value of \(N\), assuming that the licensing number of each taxi observed is equally likely to be any integer from 1 to \(N\) inclusive.
  1. The visitor observes one randomly chosen licensing number, \(X\). Using standard results for \(\sum _ { r = 1 } ^ { n } r\) and \(\sum _ { r = 1 } ^ { n } r ^ { 2 }\), show that \(\mathrm { E } ( X ) = \frac { 1 } { 2 } ( N + 1 )\) and \(\operatorname { Var } ( X ) = \frac { 1 } { 12 } \left( N ^ { 2 } - 1 \right)\). The mean of 40 independent observations of \(X\) is denoted by \(A\).
  2. Find an unbiased estimator \(E _ { 1 }\) of \(N\) based on \(A\), and state the approximate distribution of \(E _ { 1 }\), giving the value(s) of any parameter(s). \(B\) is another random variable based on a random sample of 40 independent observations of \(X\). It is given that \(\mathrm { E } ( B ) = \frac { 40 } { 27 } N\) and that \(\operatorname { Var } ( B ) = \alpha N ^ { 2 }\) where \(\alpha\) is a constant.
  3. Find an unbiased estimator \(E _ { 2 }\) of \(N\) based on \(B\), and determine the set of values of \(\alpha\) for which \(\operatorname { Var } \left( E _ { 2 } \right) > \operatorname { Var } \left( E _ { 1 } \right)\) for all values of \(N\).

6 In a certain city there are $N$ taxis. Each taxi displays a different licensing number which is an integer in the range 1 to $N$. A visitor to the city attempts to estimate the value of $N$, assuming that the licensing number of each taxi observed is equally likely to be any integer from 1 to $N$ inclusive.\\
(i) The visitor observes one randomly chosen licensing number, $X$. Using standard results for $\sum _ { r = 1 } ^ { n } r$ and $\sum _ { r = 1 } ^ { n } r ^ { 2 }$, show that $\mathrm { E } ( X ) = \frac { 1 } { 2 } ( N + 1 )$ and $\operatorname { Var } ( X ) = \frac { 1 } { 12 } \left( N ^ { 2 } - 1 \right)$.

The mean of 40 independent observations of $X$ is denoted by $A$.\\
(ii) Find an unbiased estimator $E _ { 1 }$ of $N$ based on $A$, and state the approximate distribution of $E _ { 1 }$, giving the value(s) of any parameter(s).\\
$B$ is another random variable based on a random sample of 40 independent observations of $X$. It is given that $\mathrm { E } ( B ) = \frac { 40 } { 27 } N$ and that $\operatorname { Var } ( B ) = \alpha N ^ { 2 }$ where $\alpha$ is a constant.\\
(iii) Find an unbiased estimator $E _ { 2 }$ of $N$ based on $B$, and determine the set of values of $\alpha$ for which $\operatorname { Var } \left( E _ { 2 } \right) > \operatorname { Var } \left( E _ { 1 } \right)$ for all values of $N$.

\hfill \mbox{\textit{Pre-U Pre-U 9795/2 2018 Q6}}