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OCR MEI C1 Q9
4 marks Easy -1.3
9 Expand \(\left( 1 + \frac { 1 } { 2 } x \right) ^ { 4 }\), simplifying the coefficients.
OCR MEI C1 Q10
4 marks Easy -1.2
10 Find the binomial expansion of \(\left( x + \frac { 5 } { x } \right) ^ { 3 }\), simplifying the terms.
OCR MEI C1 Q11
4 marks Easy -1.2
11
  1. Calculate \({ } ^ { 5 } \mathrm { C } _ { 3 }\).
  2. Find the coefficient of \(x ^ { 3 }\) in the expansion of \(( 1 + 2 x ) ^ { 5 }\).
OCR MEI C1 Q12
5 marks Easy -1.2
12
  1. Find the coefficient of \(x ^ { 3 }\) in the expansion of \(\left( x ^ { 2 } - 3 \right) \left( x ^ { 3 } + 7 x + 1 \right)\).
  2. Find the coefficient of \(x ^ { 2 }\) in the binomial expansion of \(( 1 + 2 x ) ^ { 7 }\).
OCR MEI C1 Q13
4 marks Moderate -0.8
13 Find the coefficient of \(x ^ { 3 }\) in the binomial expansion of \(( 5 - 2 x ) ^ { 5 }\).
OCR MEI C1 Q14
4 marks Easy -1.2
14
  1. Find the value of \({ } ^ { 8 } \mathrm { C } _ { 3 }\).
  2. Find the coefficient of \(x ^ { 3 }\) in the binomial expansion of \(\left( 1 - \frac { 1 } { 2 } x \right) ^ { 8 }\).
OCR MEI C1 Q15
4 marks Moderate -0.8
15 Find the coefficient of \(x ^ { 3 }\) in the expansion of \(( 3 - 2 x ) ^ { 5 }\).
OCR MEI C1 Q16
3 marks Easy -1.2
16 Calculate the coefficient of \(x ^ { 4 }\) in the expansion of \(( x + 5 ) ^ { 6 }\).
OCR MEI C1 Q17
4 marks Easy -1.2
17 Calculate \({ } ^ { 6 } \mathrm { C } _ { 3 }\).
Find the coefficient of \(x ^ { 3 }\) in the expansion of \(( 1 - 2 x ) ^ { 6 }\).
OCR MEI C1 Q18
4 marks Easy -1.2
18 Find the binomial expansion of \(( 2 + x ) ^ { 4 }\), writing each term as simply as possible.
OCR S3 2006 January Q1
6 marks Moderate -0.3
1 In order to judge the support for a new method of collecting household waste, a city council arranged a survey of 400 householders selected at random. The results showed that 186 householders were in favour of the new method.
  1. Calculate a 95\% confidence interval for the proportion of all householders who are in favour of the new method. A city councillor said he believed that as many householders were in favour of the new method as were against it.
  2. Comment on the councillor's belief.
OCR S3 2006 January Q2
9 marks Standard +0.3
2 A particular type of engine used in rockets is designed to have a mean lifetime of at least 2000 hours. A check of four randomly chosen engines yielded the following lifetimes in hours. $$\begin{array} { l l l l } 1896.4 & 2131.5 & 1903.3 & 1901.6 \end{array}$$ A significance test of whether engines meet the design is carried out. It may be assumed that lifetimes have a normal distribution.
  1. Give a reason why a \(t\)-test should be used.
  2. Carry out the test at the \(10 \%\) significance level.
OCR S3 2006 January Q3
7 marks Standard +0.3
3 For a restaurant with a home-delivery service, the delivery time in minutes can be modelled by a continuous random variable \(T\) with probability density function given by $$f ( t ) = \begin{cases} \frac { \pi } { 90 } \sin \left( \frac { \pi t } { 60 } \right) & 20 \leqslant t \leqslant 60 \\ 0 & \text { otherwise. } \end{cases}$$
  1. Given that \(20 \leqslant a \leqslant 60\), show that \(\mathrm { P } ( T \leqslant a ) = \frac { 1 } { 3 } \left( 1 - 2 \cos \left( \frac { \pi a } { 60 } \right) \right)\). There is a delivery charge of \(\pounds 3\) but this is reduced to \(\pounds 2\) if the delivery time exceeds a minutes.
  2. Find the value of \(a\) for which the expected value of the delivery charge for a home-delivery is £2.80.
OCR S3 2006 January Q4
11 marks Standard +0.3
4 A multi-storey car park has two entrances and one exit. During a morning period the numbers of cars using the two entrances are independent Poisson variables with means 2.3 and 3.2 per minute. The number leaving is an independent Poisson variable with mean 1.8 per minute. For a randomly chosen 10-minute period the total number of cars that enter and the number of cars that leave are denoted by the random variables \(X\) and \(Y\) respectively.
  1. Use a suitable approximation to calculate \(\mathrm { P } ( X \geqslant 40 )\).
  2. Calculate \(\mathrm { E } ( X - Y )\) and \(\operatorname { Var } ( X - Y )\).
  3. State, giving a reason, whether \(X - Y\) has a Poisson distribution.
OCR S3 2006 January Q5
12 marks Standard +0.8
5 The continuous random variable \(X\) has cumulative distribution function given by $$F ( x ) = \begin{cases} 0 & x < 1 , \\ \frac { 1 } { 8 } ( x - 1 ) ^ { 2 } & 1 \leqslant x < 3 , \\ a ( x - 2 ) & 3 \leqslant x < 4 , \\ 1 & x \geqslant 4 , \end{cases}$$ where \(a\) is a positive constant.
  1. Find the value of \(a\).
  2. Verify that \(C _ { X } ( 8 )\), the 8th percentile of \(X\), is 1.8 .
  3. Find the cumulative distribution function of \(Y\), where \(Y = \sqrt { X - 1 }\).
  4. Find \(C _ { Y } ( 8 )\) and verify that \(C _ { Y } ( 8 ) = \sqrt { C _ { X } ( 8 ) - 1 }\).
OCR S3 2006 January Q6
13 marks Standard +0.3
6 A company with a large fleet of cars compared two types of tyres, \(A\) and \(B\). They measured the stopping distances of cars when travelling at a fixed speed on a dry road. They selected 20 cars at random from the fleet and divided them randomly into two groups of 10 , one group being fitted with tyres of type \(A\) and the other group with tyres of type \(B\). One of the cars fitted with tyres of type \(A\) broke down so these tyres were tested on only 9 cars. The stopping distances, \(x\) metres, for the two samples are summarised by $$n _ { A } = 9 , \quad \bar { x } _ { A } = 17.30 , \quad s _ { A } ^ { 2 } = 0.7400 , \quad n _ { B } = 10 , \quad \bar { x } _ { B } = 14.74 , \quad s _ { B } ^ { 2 } = 0.8160 ,$$ where \(s _ { A } ^ { 2 }\) and \(s _ { B } ^ { 2 }\) are unbiased estimates of the two population variances.
It is given that the two populations have the same variance.
  1. Show that an unbiased estimate of this variance is 0.780 , correct to 3 decimal places. The population mean stopping distances for cars with tyres of types \(A\) and \(B\) are denoted by \(\mu _ { A }\) metres and \(\mu _ { B }\) metres respectively.
  2. Stating any further assumption you need to make, calculate a \(98 \%\) confidence interval for \(\mu _ { A } - \mu _ { B }\). The manufacturers of Type \(B\) tyres assert that \(\mu _ { B } < \mu _ { A } - 2\).
  3. Carry out a significance test of this assertion at the \(5 \%\) significance level. \section*{[Question 7 is printed overleaf.]}
OCR S3 2007 January Q1
6 marks Standard +0.3
1 The marks obtained by a randomly chosen student in the two papers of an examination are denoted by the random variables \(X\) and \(Y\), where \(X \sim \mathrm {~N} ( 45,81 )\) and \(Y \sim \mathrm {~N} ( 33,63 )\). The student's overall mark for the examination, \(T\), is given by \(T = X + \lambda Y\), where the constant \(\lambda\) is chosen such that \(\mathrm { E } ( T ) = 100\).
  1. Show that \(\lambda = \frac { 5 } { 3 }\).
  2. Assuming that \(X\) and \(Y\) are independent, state the distribution of \(T\), giving the values of its parameters.
  3. Comment on the assumption of independence.
OCR S3 2007 January Q2
9 marks Moderate -0.3
2 The continuous random variable \(X\) takes values in the interval \(0 \leqslant x \leqslant 3\) only with probability density function f . The graph of \(y = \mathrm { f } ( x )\) consists of the two line segments shown in the diagram. \includegraphics[max width=\textwidth, alt={}, center]{4a6d94a2-66e1-449a-ac0e-1fbada74bb3b-2_524_1287_950_429}
  1. Show that \(a = \frac { 2 } { 3 }\).
  2. Find the equations of the two line segments.
  3. Hence write down the probability density function of \(X\).
  4. Find \(\mathrm { E } ( X )\).
OCR S3 2007 January Q3
10 marks Standard +0.3
3 A new treatment of cotton thread, designed to increase the breaking strength, was tested on a random sample of 6 pieces of a standard length. The breaking strengths, in grams, were as follows. $$\begin{array} { l l l l l l } 17.3 & 18.4 & 18.6 & 17.2 & 17.5 & 19.3 \end{array}$$ The breaking strengths of a random sample of 5 similar pieces of the thread which had not been treated were as follows. \section*{\(\begin{array} { l l l l l } 18.6 & 17.2 & 16.3 & 17.4 & 16.8 \end{array}\)} A test of whether the treatment has been successful is to be carried out.
  1. State what distributional assumptions are needed.
  2. Carry out the test at the \(10 \%\) significance level.
OCR S3 2007 January Q4
10 marks Standard +0.3
4 A machine is set to produce metal discs with mean diameter 15.4 mm . In order to test the correctness of the setting, a random sample of 12 discs was selected and the diameters, \(x \mathrm {~mm}\), were measured. The results are summarised by \(\Sigma x = 177.6\) and \(\Sigma x ^ { 2 } = 2640.40\). Diameters may be assumed to be normally distributed with mean \(\mu \mathrm { mm }\).
  1. Find a \(95 \%\) confidence interval for \(\mu\).
  2. Test, at the \(5 \%\) significance level, the null hypothesis \(\mu = 15.4\) against the alternative hypothesis \(\mu < 15.4\).
OCR S3 2007 January Q5
11 marks Standard +0.3
5 Each person in a random sample of 1200 people was asked whether he or she approved of certain proposals to reduce atmospheric pollution. It was found that 978 people approved. The proportion of people in the whole population who would approve is denoted by \(p\).
  1. Write down an estimate \(\hat { p }\) of \(p\).
  2. Find a 90\% confidence interval for \(p\).
  3. Explain, in the context of the question, the meaning of a \(90 \%\) confidence interval.
  4. Estimate the sample size that would give a value for \(\hat { p }\) that differs from the value of \(p\) by less than 0.01 with probability \(90 \%\).
OCR S3 2007 January Q6
11 marks Standard +0.3
6 The lifetime of a particular machine, in months, can be modelled by the random variable \(T\) with probability density function given by $$\mathrm { f } ( t ) = \begin{cases} \frac { 3 } { t ^ { 4 } } & t \geqslant 1 \\ 0 & \text { otherwise. } \end{cases}$$
  1. Obtain the (cumulative) distribution function of \(T\).
  2. Show that the probability density function of the random variable \(Y\), where \(Y = T ^ { 3 }\), is given by \(\mathrm { g } ( y ) = \frac { 1 } { y ^ { 2 } }\), for \(y \geqslant 1\).
  3. Find \(\mathrm { E } ( \sqrt { Y } )\).
OCR S3 2007 January Q7
15 marks Standard +0.3
7 It is thought that a person's eye colour is related to the reaction of the person's skin to ultra-violet light. As part of a study, a random sample of 140 people were treated with a standard dose of ultra-violet light. The degree of reaction was classified as None, Mild or Strong. The results are given in Table 1. The corresponding expected frequencies for a \(\chi ^ { 2 }\) test of association between eye colour and reaction are shown in Table 2. \begin{table}[h]
\captionsetup{labelformat=empty} \caption{Table 1
Observed frequencies}
Eye colour
BlueBrownOtherTotal
None12171039
ReactionMild31211163
Strong2241238
Total654233140
\end{table} \begin{table}[h]
\captionsetup{labelformat=empty} \caption{Table 2
Expected frequencies}
Eye colour
BlueBrownOther
None18.1111.709.19
ReactionMild29.2518.9014.85
Strong17.6411.408.96
\end{table}
  1. (a) State suitable hypotheses for the test.
    (b) Show how the expected frequency of 18.11 in Table 2 is obtained.
    (c) Show that the three cells in the top row together contribute 4.53 to the calculated value of \(\chi ^ { 2 }\), correct to 2 decimal places.
    (d) You are given that the total calculated value of \(\chi ^ { 2 }\) is 12.78 , correct to 2 decimal places. Give the smallest value of \(\alpha\) obtained from the tables for which the null hypothesis would be rejected at the \(\alpha \%\) significance level.
  2. Test, at the \(5 \%\) significance level, whether the proportions of people in the whole population with blue eyes, brown eyes and other colours are in the ratios \(2 : 2 : 1\).
OCR S3 2008 January Q1
6 marks Standard +0.3
1 A blueberry farmer increased the amount of water sprayed over his berries to see what effect this had on their weight. The farmer weighed each of a random sample of 80 berries of the previous season's crop and each of a random sample of 100 berries of the new crop. The results are summarised in the following table, in which \(\bar { x }\) denotes the sample mean weight in grams, and \(s ^ { 2 }\) denotes an unbiased estimate of the relevant population variance.
Sample size\(\bar { x }\)\(s ^ { 2 }\)
Previous season's crop \(( P )\)801.240.00356
New crop \(( N )\)1001.360.00340
  1. Calculate an estimate of \(\operatorname { Var } \left( \bar { X } _ { N } - \bar { X } _ { P } \right)\).
  2. Calculate a \(95 \%\) confidence interval for the difference in population mean weights.
  3. Give a reason why it is unnecessary to use a \(t\)-distribution in calculating the confidence interval.
OCR S3 2008 January Q2
8 marks Standard +0.3
2 The times taken for customers' phone complaints to be handled were monitored regularly by a company. During a particular week a researcher checked a random sample of 20 complaints and the times, \(x\) minutes, taken to handle the complaints are summarised by \(\Sigma x = 337.5\). Handling times may be assumed to have a normal distribution with mean \(\mu\) minutes and standard deviation 3.8 minutes.
  1. Calculate a \(98 \%\) confidence interval for \(\mu\). During the same week two other researchers each calculated a \(98 \%\) confidence interval for \(\mu\) based on independent samples.
  2. Calculate the probability that at least one of the three intervals does not contain \(\mu\).
  3. State two ways in which the calculation in part (i) would differ if the standard deviation were unknown.