Problems

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Solution:

1. If \(n_3 = 9\) and we are looking for \(0 < n_1 < n_2 < n_3\) we can consider values for each \(n_2\). \begin{array}{clc|c} n_2 & \text{range} & \text{count} \\ \hline 6 & 4-5 & 2 \\ 7 & 3-6 & 4 \\ 8 & 2-7 & 6 \\ \hline & & 12 \end{array} When \(n_3 = 10\) \begin{array}{clc|c} n_2 & \text{range} & \text{count} \\ \hline 6 & 5 & 1 \\ 7 & 4-6 & 3 \\ 8 & 3-7 & 5 \\ 9 & 2-8 & 7 \\ \hline & & 16 \end{array} When \(n_3 = 2n+1\) we can have \(2 + 4 + \cdots + 2n-2 = n(n-1)\) When \(n_3 = 2n\) we can have \(1 + 3 + \cdots + 2n-3 = (n-1)^2\)
2. For the 3 rods to form a triangle, it suffices for the sum of the lengths of the shorter rods to be larger than \(N\). When \(N = 2n+1\) there are \(n(n-1)\) ways this can happen, out of \(\binom{2n}{2}\) ways to choos the numbers, ie \begin{align*} && P &= \frac{n(n-1)}{\frac{2n(2n-1)}{2}} \\ &&&= \frac{n-1}{2n-1} \end{align*} When \(N = 2n\) there are \((n-1)^2\) ways this can happen, out of \(\binom{2n-1}{2}\) ways, ie \begin{align*} && P &= \frac{(n-1)^2}{\frac{(2n-1)(2n-2)}{2}} \\ &&&= \frac{n-1}{2n-1} \end{align*}
3. The number of ways this can happen is: \begin{align*} C &= \sum_{k=3}^{2M+1} \# \{ \text{triangles where }k\text{ is largest} \} \\ &= \sum_{k=1}^{M} \# \{ \text{triangles where }2k+1\text{ is largest} \} +\sum_{k=1}^{M} \# \{ \text{triangles where }2k\text{ is largest} \}\\ &= \sum_{k=1}^{M} n(n-1)+\sum_{k=1}^{M} (n-1)^2\\ &= \sum_{k=1}^{M} (2n^2-3n+1)\\ &= \frac26M(M+1)(2M+1) - \frac32M(M+1) + M \\ &= \frac16 M(4M+1)(M-1) \end{align*} Therefore the probability is \begin{align*} && P &= \frac{M(4M+1)(M-1)}{6 \binom{2M+1}{3}} \\ &&&= \frac{M(4M+1)(M-1)}{(2M+1)2M(2M-1)} \\ &&&= \frac{(4M+1)(M-1)}{2(2M+1)(2M-1)} \end{align*}

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Solution: For every element in \(S\) we can choose whether or not it appears in a subset of \(S\), therefore there are \(2^n\) choices so \(2^n\) distinct subsets.

1. \(\mathbb{P}(1 \in A_1) = \frac12\) (since \(1\) is in exactly half the subsets)
2. \(\,\) \begin{align*} && \mathbb{P}(A_1 \cap A_2 = \emptyset) &= \mathbb{P}(i \not \in (A_1 \cap A_2) \forall i) \\ &&&= \prod_{i=1}^n \left ( 1-\mathbb{P}(i \in A_1 \cap A_2) \right) \\ &&&= \prod_{i=1}^n \left ( 1-\mathbb{P}(i \in A_1)\mathbb{P}(i \in \cap A_2) \right) \\ &&&= \prod_{i=1}^n \left ( 1-\frac12 \cdot \frac12\right) \\ &&&= \left (\frac34 \right)^n \end{align*}
3. \(\,\) \begin{align*} && \mathbb{P}(A_1 \cap A_2 \cap A_3 = \emptyset) &= \mathbb{P}(i \not \in (A_1 \cap A_2 \cap A_3) \forall i) \\ &&&= \prod_{i=1}^n \left ( 1-\mathbb{P}(i \in A_1 \cap A_2 \cap A_3) \right) \\ &&&= \prod_{i=1}^n \left ( 1-\mathbb{P}(i \in A_1)\mathbb{P}(i \in \cap A_2))\mathbb{P}(i \in \cap A_3) \right) \\ &&&= \prod_{i=1}^n \left ( 1-\frac12 \cdot \frac12 \cdot \frac12\right) \\ &&&= \left (\frac78 \right)^n \end{align*} Similarly, \(\displaystyle \mathbb{P}(A_1 \cap A_2 \cap \cdots \cap A_m = \emptyset) = \left ( \frac{2^m-1}{2^m} \right)^n\)
4. \(\,\) \begin{align*} && \mathbb{P}(A_1 \subseteq A_2) &= \mathbb{P}(A_1 \cap A_2^c = \emptyset) \\ &&&= \left (\frac34 \right)^n \\ \\ && \mathbb{P}(A_1 \subseteq A_2 \subseteq A_3) &= \prod_{i=1}^n \mathbb{P}(\text{once }i\text{ appears it keeps appearing}) \\ &&&= \prod_{i=1}^n \frac{\#\{(0,0,0), (0,0,1), (0,1,1), (1,1,1) \}}{2^3} \\ &&&= \prod_{i=1}^n \frac{4}{8} \\ &&&= \frac{1}{2^n} \\ \\ && \mathbb{P}(A_1 \subseteq A_2 \subseteq \cdots \subseteq A_m) &= \prod_{i=1}^n \frac{m+1}{2^m} \\ &&&= \left ( \frac{m+1}{2^m} \right)^n \end{align*}

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Solution: Every \(T_7\) triangle is valid, so we are interested in new triangles which have \(8\) has a longest side. We can have: \begin{array}{c|c|c} \text{longest} & \text{middle} & \text{shortest} \\ \hline 8 & 7 & 1-6 \\ 8 & 6 & 2-5 \\ 8 & 5 & 3-4 \end{array} which is \(6+4+2\) extra triangles. The new ones excluding all the sixes are: \begin{array}{c|c|c} \text{longest} & \text{middle} & \text{shortest} \\ \hline 8 & 7 & 1-6 \\ 8 & 6 & 2-5 \\ 8 & 5 & 3-4 \\ 7 & 6 & 1-5 \\ 7 & 5 & 2-4 \\ 7 & 4 & 3 \\ \end{array} Ie \(2+4+6 + 1 + 3+5\) \(T_{2m}-T_{2m-1} = 2 \frac{(m-1)m}{2} = m(m-1)\) and \(T_{2m}-T_{2m-2} = \frac{(2m-2)(2m-1)}{2}\) \(T_4 = 3\) (\(1,2,3\), \(1,3,4\), \(2,3,4\)) and \(\frac16 \cdot 2 \cdot 1 \cdot 9 = 3\) so the base case holds. Suppose it's true for some \(m = k\), then \begin{align*} && T_{2(k+1)} &= T_{2k} + \frac{2m(2m+1)}{2} \\ &&&= \frac{m(m-1)(4m+1)}{6} + \frac{6m(2m+1)}{6}\\ &&&= \frac{m(4m^2-3m-1+12m+6)}{6} \\ &&&= \frac{m(4m^2+9m+5)}{6}\\ &&&= \frac{m(4m+5)(m+1)}{6}\\ &&&= \frac{(m+1-1)(4(m+1)+5)(m+1)}{6}\\ \end{align*} as required, therefore it is true by induction. For odd numbers, we can see that \(T_{2m-1} = \frac{m(m-1)(4m+1)}{6} - m(m-1) = \frac{m(m-1)(4m-5)}{6}\)

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Solution: We are choosing any \(5\) digit number from \(\{1,2,3,4,5\}\). There are \(5^5\) such numbers. \begin{align*} && \mathbb{E}(\text{different digits}) &= \frac1{5^5} \left (1 \cdot 5 + 2 \cdot \binom{5}{2}(2^5-2)+3 \cdot \binom{5}{3}(3^5-3 \cdot 2^5+3)+4 \cdot \binom{5}{4}(4^5 - 4 \cdot 3^5+6 \cdot 2^5-4) + 5 \cdot 5! \right) \\ &&&= \frac{2101}{625} = 3.3616 \end{align*}

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Solution:

1. For each number from \(1\) to \(8\) (4+4), we can count the number of ways it can be achieved in any way, or without including a leading \(0\). \begin{array}{c|c|c|c} \text{total} & \text{ways with }0 & \text{ways without } 0 & \text{comb}\\ \hline 8 & 1 & 1 & 1\\ 7 & 2 & 2 & 4 \\ 6 & 3 & 3 & 9 \\ 5 & 4 & 4 & 16 \\ 4 & 5 & 4 & 20 \\ 3 & 4 & 3 & 12 \\ 2 & 3 & 2 & 6 \\ 1 & 2 & 1 & 2 \\ \hline &&& 70 \end{array}
2. For \(2k\) to \(k+1\) there are \(1 \times 1 + 2 \times 2 + \cdots i\times i+\cdots + k\times k\) ways to achieve this, (we can choose anything from \(k\) to \(k-i+1\) for the first digit, and we can never have a \(0\). For \(1\) to \(k\) we can have \(1 \times 2 + 2 \times 3 + \cdots + k \times (k+1)\) since we cannot start with a \(0\), but can have anything less than or equal to \(i\) for the first digit, and then with the \(0\) we can have the same thing starting with \(0\). Hence the answer is: \begin{align*} && S &= \sum_{i=1}^k i^2 + \sum_{i=1}^k i (i+1) \\ &&&= 2\sum_{i=1}^k i^2 + \sum_{i=1}^k i \\ &&&= \frac{1}{3} k(k+1)(2k+1) + \frac12k(k+1) \\ &&&= k(k+1) \left (\frac{2k+1}{3} + \frac{1}{2} \right) \\ &&&= \frac16 k(k+1)(4k+2+3) \\ &&&= \frac16 k(k+1)(4k+5) \end{align*}

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Solution: There are many ways to do the counting in each question, possibly the clearest way is to always consider the order in which discs are taken, although all methods should work equally well. For some examples Bayes rule also offers a fast solution.

1. There are we are choose \(4\) objects in order from \(5\) (ie \({^5\P_4}\)) to obtain valid draws, this is out of a total of picking \(4\) objects from \(11\) (\({^{11}\P_4}\)). Ie the probability is: \(\displaystyle \frac{{^5\P_4}}{{^{11}\P_4}} = \frac{5! \cdot 7!}{11!} = \frac{1}{66}\) Alternatively, there are \(\binom{5}{4}\) ways to choose four numbered discs, out of \(\binom{11}{4}\) ways to choose four discs. ie \(\displaystyle \binom{5}{4} \Big / \binom{11}{4} = \frac{5 \cdot 4! \cdot 7!}{11!} = \frac{5 \cdot 4 \cdot 3 \cdot 2}{11 \cdot 10 \cdot 9 \cdot 8} = \frac1{66}\)
2. \begin{align*} \mathbb{P}(\text{all four discs are numbered} | \text{first disc is 3}) &= \frac{\mathbb{P}(\text{all four discs are numbered and first disc is 3})}{\mathbb{P}( \text{first disc is 3})} \\ &= \frac{^4\P_3 \big / {^{11}\P_4}}{1/11} \\ &= 11\cdot \frac{4!}{1!} \Bigg / \frac{11!}{7!} \\ &= \frac{4! \cdot 7! \cdot 11}{11!} \\ &= \frac{4\cdot 3 \cdot 2}{10 \cdot 9 \cdot 8} \\ &= \frac{1}{30} \end{align*} Alternatively, \begin{align*} \mathbb{P}(\text{all four discs are numbered} | \text{first disc is 3}) &= \frac{\mathbb{P}(\text{all four discs are numbered and first disc is 3})}{\mathbb{P}( \text{first disc is 3})} \\ &= \frac{\binom{4}{3} \Bigg / 11 \cdot \binom{10}{3}}{1/11} \\ &= \frac{1}{30} \end{align*} Where we are calculating this as "choose one number", then "choose 3 more", which can happen ending up with 3, number, number, number in \(\binom{4}{3}\) ways, and there are \(11 \cdot \binom{10}{3}\) was overall. Another alternative using Bayes rule: \begin{align*} \mathbb{P}(\text{all four discs are numbered} | \text{first disc is 3}) &= \mathbb{P}( \text{first disc is 3} | \text{all four discs are numbered}) \frac{ \mathbb{P}( \text{all four discs are numbered} }{ \mathbb{P}( \text{first disc is 3} )} \\ &= \frac{\frac{1}{5} \cdot \frac{1}{66}}{\frac{1}{11}} \\ &= \frac1{30} \end{align*}
3. \begin{align*} \mathbb{P}(\text{exactly two discs are numbered} | \text{first disc is 3}) &=\frac{\mathbb{P}(\text{exactly two discs are numbered and first disc is 3})}{\mathbb{P}( \text{first disc is 3})} \\ &= \frac{3 \cdot {^4\P_1} \cdot {^{6}\P_2} \big / {^{11}\P_4}}{\frac1{11} } \\ &= \frac12 \end{align*} Alternatively, \begin{align*} \mathbb{P}(\text{exactly two discs are numbered} | \text{first disc is 3}) &=\frac{\mathbb{P}(\text{exactly two discs are numbered and first disc is 3})}{\mathbb{P}( \text{first disc is 3})} \\ &= \frac{\binom{4}{1}\binom{6}{2} \Big / 11 \cdot \binom{10}{3}}{1/11} \\ &= \frac12 \end{align*}
4. \begin{align*} \mathbb{P}(\text{exactly two discs are numbered} | \text{3 taken}) &= \frac{\mathbb{P}(\text{exactly two discs are numbered and 3 taken})}{\mathbb{P}( \text{3 taken})} \\ &= \frac{\binom{4}{1}\binom{6}{2} \Big / \binom{11}{4}}{\frac{4}{11}} \\ &= \frac{\frac{2}{11}}{\frac4{11}} \\ &= \frac12 \end{align*} Using Bayes rule: \(\mathbb{P}( \text{3 taken}) = \frac{1}{11} + \frac{10}{11}\frac{1}{10} + \frac{10}{11}\frac{9}{10}\frac{1}{9} + \frac{10}{11}\frac{9}{10}\frac89\frac18 = \frac{4}{11}\) \begin{align*} \mathbb{P}(\text{exactly two discs are numbered} | \text{3 taken}) &= \frac{\mathbb{P}(\text{3 taken | exactly two discs are numbered})\mathbb{P}(\text{exactly two discs are numbered})}{\mathbb{P}( \text{3 taken})} \\ &= \frac{\frac{4}{10} \cdot \binom{5}{2} \binom{6}{2} \Big / \binom{11}{4}}{4/11} \\ &= \frac{\frac4{10}{5 / 11}}{4/11} \\ &= \frac{1}{2} \end{align*}
5. \begin{align*} \mathbb{P}(\text{exactly two discs are numbered} | \text{numbered disc first}) &= \frac{\mathbb{P}(\text{exactly two discs are numbered and numbered disc first})}{\mathbb{P}( \text{numbered disc first})} \\ &= \frac{3 \cdot {^5\P_1}\cdot{^4\P_1}\cdot{^6\P_2} \Big / {^{11}\P_4}}{\frac{5}{11}} \\ &= \frac{1}{2} \end{align*}
6. \begin{align*} \mathbb{P}(\text{exactly two discs are numbered} | \text{numbered disc taken}) &= \frac{\mathbb{P}(\text{exactly two discs are numbered and numbered disc taken})}{\mathbb{P}(\text{numbered disc taken})} \\ &= \frac{\mathbb{P}(\text{exactly two discs are numbered})}{1 - \mathbb{P}(\text{not numbered discs taken})} \\ &= \frac{\binom{5}{2}\binom{6}{2} \Big / \binom{11}{4}}{1 - \binom{6}{4} \Big / \binom{11}{4}} \\ &= \frac{\frac{5}{11}}{\frac{21}{22}} \\ &= \frac{10}{21} \neq \frac12 \end{align*}

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Solution: There are \(1\,000\,000\) numbers between 1 and a million (inclusive). \(500\,000\) are divisible by \(2\), \(200\,000\) are divisible by \(5\) and \(100\,000\) are divisible by both. Therefore there are: \(1\,000\,000 - 500\,000-200\,000+100\,000 = 400\,000\). (Alternatively, the only numbers are those which are \(1,3,7,9 \pmod{10}\) so there are \(4\) every \(10\), or \(4 \cdot 100\,000\)). We can sum all these values similarly, \begin{align*} S &= \underbrace{\sum_{i=1}^{10^6} i}_{\text{all numbers}}-\underbrace{\sum_{i=1}^{5 \cdot 10^5} 2i}_{\text{all multiples of } 2}-\underbrace{\sum_{i=1}^{2 \cdot 10^5} 5i}_{\text{all multiples of } 5}+\underbrace{\sum_{i=1}^{10^5} 10i}_{\text{all multiples of } 5} \\ &= \frac{10^6 \cdot (10^6 + 1)}{2} - \frac{10^6 \cdot (5\cdot 10^5+1)}{2} - \frac{10^6 \cdot (2\cdot 10^5+1)}{2} + \frac{10^6 \cdot (10^5+1)}{2} \\ &= \frac{10^6 (10^5 \cdot (10-5-2+1))))}{2} \\ &= \frac{10^6 \cdot 10^5 \cdot 4}{2} \\ &= 2\cdot 10^{11} \end{align*} So the average value is \(\frac{2 \cdot 10^{11}}{4 \cdot 10^5} = \frac{10^6}{2} = 500\,000\). (Alternatively, each value can be paired off eg \(999\,999\) with \(1\) and so on, leaving averages of \(500\,000\)). Note that \(4197\) is divisible by \(3\) and \(7\). Using the same long we have: \(4179 - \frac{4179}{3} - \frac{4179}{7} + \frac{4179}{21} = 4179 - 1393 - 597 + 199 = 2388\). The sum will be: \begin{align*} S &= \underbrace{\sum_{i=1}^{4179}i }_{\text{all numbers}}- \underbrace{\sum_{i=1}^{1393}3i }_{\text{multiples of }3}- \underbrace{\sum_{i=1}^{597}7i }_{\text{multiples of }7}+ \underbrace{\sum_{i=1}^{199}21i }_{\text{mulitples of }21} \\ &= \frac{4179 \cdot 4180}{2} - \frac{4179 \cdot 1394}{2} - \frac{4179 \cdot 598}{2} +\frac{4179 \cdot 200}{2} \\ &= \frac{4179 \cdot 2388}{2} \end{align*} So the average value is \(\frac{4179}{2}\).

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Solution: First consider \(5\) digit numbers containing at most \(2\) non-zero digits. Then there are \(\binom{9}{2}\) ways to choose the two digits, and \(2^{5}-2\) different ways to arrange them, removing the ones which are all the same. Considering all the pairs including zero, there are \(9\) ways to choose the non-zero (first) digit. There are \(2^4-1\) remaining digits where not all the numbers are the same. Finally we must not forget \(100\,000\). Therefore there are \(\binom{9}{2}(2^5-2) +9\cdot(2^4-1) + 1 = 1216\)

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Solution: Writing out the possibilities in order of the largest coin used (and then second largest and so-on): \begin{align*} && 10 &= 10 \\ &&&= 5 + 5 \\ &&&= 5 + 2 + 2 + 1 \\ &&&= 5 + 2 + 1 + 1 + 1 \\ &&&= 5 + 1 + 1 + 1 + 1 + 1\\ &&&= 2 + 2 + 2 + 2 + 2 = 5 \cdot 2\\ &&&= 4 \cdot 2 + 2 \cdot 1 \\ &&&= 3 \cdot 2 + 4 \cdot 1\\ &&&= 2 \cdot 2 + 6\cdot 1\\ &&&= 1 \cdot 2 + 8\cdot 1 \\ &&&= 10 \cdot 1 \end{align*} For 20p, we have \begin{align*} && 20 &= 20 \\ &&&= 10 + \text{all 11 ways} \\ &&&= 4\cdot 5 \\ &&&= 3\cdot 5 +\text{3 ways} \\ &&&= 2\cdot5 + \text{6 ways} \\ &&&= 1\cdot 5 + \text{8 ways} \\ &&&= k\cdot 2 + (20-2k)\cdot 1 \quad \text{11 ways} \end{align*} ie 41 ways

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Solution:

1. \(\frac{2}{28} = \frac{1}{14}\)
2. \(1-\frac{27}{28}\frac{26}{27}\frac{25}{26} = \frac{3}{28}\)
3. \(1 - \frac{26}{28}\frac{25}{27}\frac{24}{26} = \frac{13}{63}\)
4. \(1-\frac{26}{27}\frac{25}{26} = \frac{2}{27}\)
5. \(\frac{1}{27}\)
6. There are \(\binom{2}{1} \binom{26}{2} + \binom{2}{2}\binom{26}{1}\) ways to choose at least one single sex college and \( \binom{2}{2}\binom{26}{1}\) ways to choose both, therefore \begin{align*} P &= \frac{ \binom{2}{2}\binom{26}{1}}{\binom21 \binom{26}2+ \binom{2}{2}\binom{26}{1}} \\ &= \frac{26}{2\cdot \frac{26\cdot25}{2}+26 }\\ &= \frac{1}{25+1} = \frac{1}{26} \end{align*}

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Solution: Suppose we have \(a = 2k\), it is necessary (by the triangle inequality) that \(b + c > a\). So the smallest \(b\) can be is \(k+1\), and then \(c\) must be \(k\) (1 choice). Then \(b\) could be \(k+2\) and \(c\) can be \(k+1\), \(k\), \(k-1\) (3 choices). Suppose \(b = k+i\) then \(c\) can be \(k+i-1, \ldots, k-i+1\) which is \(2i-1\) choices. This works until \(b = 2k-1\) and there are \(2(k-1)-1 = 2k-3 = a-3\) choices. Therefore there are \(1 + 3 + 5 + \cdots + (a-3)\) total choices. If \(a = 2k+1\) then, \(b = k+1\) is not possible \(b = k+2\) we have \(a = k+1, k\) (2 choices) \(b = k+3\) we have \(a = k+2, k+1, k, k-1\) (4 choices) \(b = k + i\) we have \(a = k+i-1, \cdots, k-i+2\) (\(2i-2\) choices) This works until \(b = k+k\) with \(2k-2 = a-3\) choices. So \(2 + 4 + \cdots + (a-3)\) If \(a\) is even, we have \(\left ( \frac{a-2}{2} \right)^2\) If \(a\) is odd we have \(\frac{(a-3)(a-1)}{4}\) Therefore the total number is: \begin{align*} C &= \sum_{k=2}^N \left ( \frac{(2k-2)^2}{4} + \frac{(2k+1-3)(2k+1-1)}{4} \right) \\ &= \sum_{k=2}^N \left ( (k-1)^2 + (k-1)k\right) \\ &= \sum_{k=2}^N (2k^2-3k+1) \\ &= \sum_{k=1}^N (2k^2-3k+1) \\ &= \frac{N(N+1)(2N+1)}{3} - \frac{3N(N+1)}{2} + N \\ &= \frac{N((N+1)(4N+2-9)+6)}{6} \\ &= \frac{N(4N+1)(N-1)}{6} \\ \end{align*} When \(N = 3\) we have \(1, 2, \cdots, 7\) sticks, and so \(a = 4\), \(1\) option \(a = 5\), \(2\) options \(a = 6\) \(4\) options \(a = 7\) \(6\) options for a total of \(13\). \(\frac{3 \cdot 13 \cdot 2}{6} = 13\) so this is promising, There are \(\binom{2N+1}{3}\) ways to choose three sticks (in order) and of those our formula tells us how many are valid, therefore \begin{align*} && P &= \frac{ \frac{N(4N+1)(N-1)}{6} }{\frac{(2N+1)2N(2N-1)}{6}} \\ &&&= \frac{(4N+1)(N-1)}{2(4N^2-1)} \end{align*}

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Solution:

1. There are \(m \cdot n\) line segments, since each of the \(m\) points on the \(y\)-axis correspond to \(n\) points of the \(x\)-axis.
2. Every pair of points on the \(x\)-axis and pair of points on the \(y\) axis will generate \(4\) lines, but only \(1\) of those points will meet in the middle, therefore there will be \(\binom{m}{2} \binom{n}{2}\) intersections.

The segment joining the smallest \(x\) to the smallest \(y\) and the segment joining the largest \(x\) to the largest \(y\) will not meet any other segments. The segment joining the smallest \(x\) to the largest \(y\) and the segment joining the largest \(x\) to the smallest \(y\) will have the largest number of intersections. They each intersect all the other segment coming out of other points (except the ones headed for the same point) ie \((m-1)(n-1)\) each. They also intersect each other, so \(2(m-1)(n-1)-1\) points. Therefore we are interested in: \begin{align*} \frac{\binom{n}{2}\binom{n}{2} - 2(n-1)^2+1}{n^2-4} &= \frac{\frac{n^2(n-1)^2}{4} - 2n^2+4n-1}{n^2-4} \\ &= \frac{n^4-2n^3+n^2-8n^2+16n-4}{4(n^2-4)} \\ &= \frac{(n - 2) (n^3 - 7 n + 2)}{4(n^2-4)} \\ &= \frac{n^3-7n+3}{4(n+2)} \end{align*}