1998 Paper 3 Q13

Year: 1998
Paper: 3
Question Number: 13

Course: LFM Stats And Pure
Section: Conditional Probability

Difficulty: 1700.0 Banger: 1500.0

Problem

Write down the probability of obtaining \(k\) heads in \(n\) tosses of a fair coin. Now suppose that \(k\) is known but \(n\) is unknown. A maximum likelihood estimator (MLE) of \(n\) is defined to be a value (which must be an integer) of \(n\) which maximizes the probability of \(k\) heads. A friend has thrown a fair coin a number of times. She tells you that she has observed one head. Show that in this case there are two MLEs of the number of tosses she has made. She now tells you that in a repeat of the exercise she has observed \(k\) heads. Find the two MLEs of the number of tosses she has made. She next uses a coin biased with probability \(p\) (known) of showing a head, and again tells you that she has observed \(k\) heads. Find the MLEs of the number of tosses made. What is the condition for the MLE to be unique?

Solution

\begin{align*} && \mathbb{P}(k \text{ heads} | n\text{ tosses}) &= \binom{n}k 2^{-n} \\ && \mathbb{P}(1 \text{ head} | n\text{ tosses}) &= n2^{-n} \\ \Rightarrow && \frac{ \mathbb{P}(1 \text{ head} | n+1\text{ tosses}) }{ \mathbb{P}(1 \text{ head} | n\text{ tosses}) } &= \frac{n+1}{2n} \end{align*} Which is less than \(1\) unless \(n \geq 1\). Therefore the MLE is \(n = 1\) or \(n= 2\). \begin{align*} \frac{ \mathbb{P}(k \text{ head} | n+1\text{ tosses}) }{ \mathbb{P}(k \text{ head} | n\text{ tosses}) } &= \frac{\binom{n+1}{k}}{2 \binom{n}{k}} \\ &= \frac{(n+1)!(n-k)!}{2n!(n+1-k)!} \\ &= \frac{n+1}{2(n+1-k)} \end{align*} This is less than or equal to \(1\) if \(n+1 = 2(n+1-k) \Leftrightarrow n= 2k-1\), therefore the MLEs are \(2k-1\) and \(2k\). If the coin is biased, we have \begin{align*} && \frac{ \mathbb{P}(k \text{ head} | n+1\text{ tosses}) }{ \mathbb{P}(k \text{ head} | n\text{ tosses}) } &= \frac{\binom{n+1}{k}p^kq^{n+1-k}}{\binom{n}{k}p^kq^{n-k}} \\ &&&= \frac{n+1}{(n+1-k)}q \\ \\ && 1 & \geq \frac{n+1}{(n+1-k)}q \\ \Leftrightarrow && (n+1)(1-q) &\geq k \\ \Leftrightarrow && n+1 & \geq \frac{k}{p} \end{align*} Therefore the probability is increasing until \(n+1 \geq \frac{k}{p}\). If \(\frac{k}p\) is an integer the MLEs are \(\frac{k}{p}-1\) and \(\frac{k}p\), otherwise it is \(\lfloor \frac{k}{p} \rfloor\) and the MLE is unique.
Rating Information

Difficulty Rating: 1700.0

Difficulty Comparisons: 0

Banger Rating: 1500.0

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Problem source
Write down the probability of obtaining $k$ heads in $n$ tosses of a fair coin. Now suppose that $k$ is known but $n$ is unknown. A \textit{maximum likelihood estimator} (MLE) of $n$ is defined to be a value (which must be an integer) of $n$ which maximizes the probability of $k$ heads.
A friend has thrown a fair coin a number of times. She tells you that she has observed one head. Show that in this case there are \textit{two} MLEs of the number of tosses she has made. She now tells you that in a repeat of the exercise she has observed $k$ heads.  Find the two MLEs of the number of tosses she has made.  She next uses a coin biased with probability $p$ (known) of showing a head, and again tells you that she has observed $k$ heads. Find the MLEs of the number of tosses made. What is the condition for the MLE to be unique?
Solution source
\begin{align*}
&& \mathbb{P}(k \text{ heads} |  n\text{ tosses}) &= \binom{n}k 2^{-n} \\
&& \mathbb{P}(1 \text{ head} |  n\text{ tosses}) &= n2^{-n} \\
\Rightarrow && \frac{ \mathbb{P}(1 \text{ head} |  n+1\text{ tosses}) }{ \mathbb{P}(1 \text{ head} |  n\text{ tosses}) } &= \frac{n+1}{2n}
\end{align*}

Which is less than $1$ unless $n \geq 1$. Therefore the MLE is $n = 1$ or $n= 2$.

\begin{align*}
 \frac{ \mathbb{P}(k \text{ head} |  n+1\text{ tosses}) }{ \mathbb{P}(k \text{ head} |  n\text{ tosses}) } &= \frac{\binom{n+1}{k}}{2 \binom{n}{k}} \\
&= \frac{(n+1)!(n-k)!}{2n!(n+1-k)!} \\
&= \frac{n+1}{2(n+1-k)}
\end{align*}

This is less than or equal to $1$ if $n+1 = 2(n+1-k) \Leftrightarrow n= 2k-1$, therefore the MLEs are $2k-1$ and $2k$.

If the coin is biased, we have

\begin{align*}
&&  \frac{ \mathbb{P}(k \text{ head} |  n+1\text{ tosses}) }{ \mathbb{P}(k \text{ head} |  n\text{ tosses}) } &= \frac{\binom{n+1}{k}p^kq^{n+1-k}}{\binom{n}{k}p^kq^{n-k}} \\
&&&= \frac{n+1}{(n+1-k)}q \\ 
\\
&& 1 & \geq \frac{n+1}{(n+1-k)}q \\
\Leftrightarrow && (n+1)(1-q) &\geq k \\
\Leftrightarrow && n+1 & \geq \frac{k}{p}
\end{align*}

Therefore the probability is increasing until $n+1 \geq \frac{k}{p}$. If $\frac{k}p$ is an integer the MLEs are $\frac{k}{p}-1$ and $\frac{k}p$, otherwise it is $\lfloor \frac{k}{p} \rfloor$ and the MLE is unique.