Questions S3 (621 questions)

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OCR S3 2011 June Q7
15 marks Standard +0.3
7 In order to improve their mathematics results 10 students attended an intensive Summer School course. Each student took a test at the start of the course and a similar test at the end of the course. The table shows the scores achieved in each test.
Student12345678910
First test score37273847542752396223
Second test score47295044723763457632
It is desired to test whether there has been an increase in the population mean score.
  1. Explain why a two-sample \(t\)-test would not be appropriate.
  2. Stating any necessary assumptions, carry out a suitable \(t\)-test at the \(\frac { 1 } { 2 } \%\) significance level.
  3. The Summer School director claims that after taking the course the population mean score increases by more than 5 . Is there sufficient evidence for this claim?
OCR S3 Specimen Q1
5 marks Standard +0.8
1 A car repair firm receives call-outs both as a result of breakdowns and also as a result of accidents. On weekdays (Monday to Friday), call-outs resulting from breakdowns occur at random, at an average rate of 6 per 5 -day week; call-outs resulting from accidents occur at random, at an average rate of 2 per 5 -day week. The two types of call-out occur independently of each other. Find the probability that the total number of call-outs received by the firm on one randomly chosen weekday is more than 3 .
OCR S3 Specimen Q2
7 marks Standard +0.3
2 Boxes of matches contain 50 matches. Full boxes have mean mass 20.0 grams and standard deviation 0.4 grams. Empty boxes have mean mass 12.5 grams and standard deviation 0.2 grams. Stating any assumptions that you need to make, calculate the mean and standard deviation of the mass of a match. [7]
OCR S3 Specimen Q3
8 marks Standard +0.3
3 A random sample of 80 precision-engineered cylindrical components is checked as part of a quality control process. The diameters of the cylinders should be 25.00 cm . Accurate measurements of the diameters, \(x \mathrm {~cm}\), for the sample are summarised by $$\Sigma ( x - 25 ) = 0.44 , \quad \Sigma ( x - 25 ) ^ { 2 } = 0.2287 .$$
  1. Calculate a \(99 \%\) confidence interval for the population mean diameter of the components.
  2. For the calculation in part (i) to be valid, is it necessary to assume that component diameters are normally distributed? Justify your answer.
OCR S3 Specimen Q4
10 marks Standard +0.3
4 The lengths of time, in seconds, between vehicles passing a fixed observation point on a road were recorded at a time when traffic was flowing freely. The frequency distribution in Table 1 is a summary of the data from 100 observations. \begin{table}[h]
Time interval \(( x\) seconds \()\)\(0 < x \leqslant 5\)\(5 < x \leqslant 10\)\(10 < x \leqslant 20\)\(20 < x \leqslant 40\)\(40 < x\)
Observed frequency49222072
\captionsetup{labelformat=empty} \caption{Table 1}
\end{table} It is thought that the distribution of times might be modelled by the continuous random variable \(X\) with probability density function given by $$f ( x ) = \begin{cases} 0.1 e ^ { - 0.1 x } & x > 0 \\ 0 & \text { otherwise } \end{cases}$$ Using this model, the expected frequencies (correct to 2 decimal places) for the given time intervals are shown in Table 2. \begin{table}[h]
Time interval \(( x\) seconds \()\)\(0 < x \leqslant 5\)\(5 < x \leqslant 10\)\(10 < x \leqslant 20\)\(20 < x \leqslant 40\)\(40 < x\)
Expected frequency39.3523.8723.2511.701.83
\captionsetup{labelformat=empty} \caption{Table 2}
\end{table}
  1. Show how the expected frequency of 23.87, corresponding to the interval \(5 < x \leqslant 10\), is obtained.
  2. Test, at the 10\% significance level, the goodness of fit of the model to the data.
OCR S3 Specimen Q5
13 marks Standard +0.8
5 The continuous random variable \(X\) has a triangular distribution with probability density function given by $$f ( x ) = \left\{ \begin{array} { l r } 1 + x & - 1 \leqslant x \leqslant 0 \\ 1 - x & 0 \leqslant x \leqslant 1 \\ 0 & \text { otherwise } \end{array} \right.$$
  1. Show that, for \(0 \leqslant a \leqslant 1\), $$\mathrm { P } ( | X | \leqslant a ) = 2 a - a ^ { 2 } .$$ The random variable \(Y\) is given by \(Y = X ^ { 2 }\).
  2. Express \(\mathrm { P } ( Y \leqslant y )\) in terms of \(y\), for \(0 \leqslant y \leqslant 1\), and hence show that the probability density function of \(Y\) is given by $$g ( y ) = \frac { 1 } { \sqrt { } y } - 1 , \quad \text { for } 0 < y \leqslant 1 .$$
  3. Use the probability density function of \(Y\) to find \(\mathrm { E } ( Y )\), and show how the value of \(\mathrm { E } ( Y )\) may also be obtained directly using the probability density function of \(X\).
  4. Find \(\mathrm { E } ( \sqrt { } Y )\).
OCR S3 Specimen Q6
14 marks Moderate -0.3
6 Certain types of food are now sold in metric units. A random sample of 1000 shoppers was asked whether they were in favour of the change to metric units or not. The results, classified according to age, were as shown in the table.
\cline { 2 - 4 } \multicolumn{1}{c|}{}Age of shopper
\cline { 2 - 4 } \multicolumn{1}{c|}{}Under 3535 and overTotal
In favour of change187161348
Not in favour of change283369652
Total4705301000
  1. Use a \(\chi ^ { 2 }\) test to show that there is very strong evidence that shoppers' views about changing to metric units are not independent of their ages.
  2. The data may also be regarded as consisting of two random samples of shoppers; one sample consists of 470 shoppers aged under 35 , of whom 187 were in favour of change, and the second sample consists of 530 shoppers aged 35 or over, of whom 161 were in favour of change. Determine whether a test for equality of population proportions supports the conclusion in part (i).
OCR S3 Specimen Q7
15 marks Standard +0.3
7 A factory manager wished to compare two methods of assembling a new component, to determine which method could be carried out more quickly, on average, by the workforce. A random sample of 12 workers was taken, and each worker tried out each of the methods of assembly. The times taken, in seconds, are shown in the table.
Worker\(A\)\(B\)\(C\)\(D\)\(E\)\(F\)\(G\)\(H\)\(I\)\(J\)\(K\)\(L\)
Time in seconds for Method 1483847596241505258544960
Time in seconds for Method 2474038555742424062474751
  1. (a) Carry out an appropriate \(t\)-test, using a \(2 \%\) significance level, to test whether there is any difference in the times for the two methods of assembly.
    (b) State an assumption needed in carrying out this test.
    (c) Calculate a \(95 \%\) confidence interval for the population mean time difference for the two methods of assembly.
  2. Instead of using the same 12 workers to try both methods, the factory manager could have used two independent random samples of workers, allocating Method 1 to the members of one sample and Method 2 to the members of the other sample.
    (a) State one disadvantage of a procedure based on two independent random samples.
    (b) State any assumptions that would need to be made to carry out a \(t\)-test based on two independent random samples.
OCR MEI S3 2007 January Q1
18 marks Standard +0.3
1 The continuous random variable \(X\) has probability density function $$f ( x ) = k ( 1 - x ) \quad \text { for } 0 \leqslant x \leqslant 1$$ where \(k\) is a constant.
  1. Show that \(k = 2\). Sketch the graph of the probability density function.
  2. Find \(\mathrm { E } ( X )\) and show that \(\operatorname { Var } ( X ) = \frac { 1 } { 18 }\).
  3. Derive the cumulative distribution function of \(X\). Hence find the probability that \(X\) is greater than the mean.
  4. Verify that the median of \(X\) is \(1 - \frac { 1 } { \sqrt { 2 } }\).
  5. \(\bar { X }\) is the mean of a random sample of 100 observations of \(X\). Write down the approximate distribution of \(\bar { X }\).
OCR MEI S3 2007 January Q2
18 marks Standard +0.3
2 The manager of a large country estate is preparing to plant an area of woodland. He orders a large number of saplings (young trees) from a nursery. He selects a random sample of 12 of the saplings and measures their heights, which are as follows (in metres). $$\begin{array} { l l l l l l l l l l l l } 0.63 & 0.62 & 0.58 & 0.56 & 0.59 & 0.62 & 0.64 & 0.58 & 0.55 & 0.61 & 0.56 & 0.52 \end{array}$$
  1. The manager requires that the mean height of saplings at planting is at least 0.6 metres. Carry out the usual \(t\) test to examine this, using a \(5 \%\) significance level. State your hypotheses and conclusion carefully. What assumption is needed for the test to be valid?
  2. Find a \(95 \%\) confidence interval for the true mean height of saplings. Explain carefully what is meant by a \(95 \%\) confidence interval.
  3. Suppose the assumption needed in part (i) cannot be justified. Identify an alternative test that the manager could carry out in order to check that the saplings meet his requirements, and state the null hypothesis for this test.
OCR MEI S3 2007 January Q3
18 marks Standard +0.3
3 Bill and Ben run their own gardening company. At regular intervals throughout the summer they come to work on my garden, mowing the lawns, hoeing the flower beds and pruning the bushes. From past experience it is known that the times, in minutes, spent on these tasks can be modelled by independent Normally distributed random variables as follows.
MeanStandard deviation
Mowing444.8
Hoeing322.6
Pruning213.7
  1. Find the probability that, on a randomly chosen visit, it takes less than 50 minutes to mow the lawns.
  2. Find the probability that, on a randomly chosen visit, the total time for hoeing and pruning is less than 50 minutes.
  3. If Bill mows the lawns while Ben does the hoeing and pruning, find the probability that, on a randomly chosen visit, Ben finishes first. Bill and Ben do my gardening twice a month and send me an invoice at the end of the month.
  4. Write down the mean and variance of the total time (in minutes) they spend on mowing, hoeing and pruning per month.
  5. The company charges for the total time spent at 15 pence per minute. There is also a fixed charge of \(\pounds 10\) per month. Find the probability that the total charge for a month does not exceed \(\pounds 40\).
OCR MEI S3 2007 January Q4
18 marks Standard +0.3
4
  1. An amateur weather forecaster has been keeping records of air pressure, measured in atmospheres. She takes the measurement at the same time every day using a barometer situated in her garden. A random sample of 100 of her observations is summarised in the table below. The corresponding expected frequencies for a Normal distribution, with its two parameters estimated by sample statistics, are also shown in the table.
    Pressure ( \(a\) atmospheres)Observed frequencyFrequency as given by Normal model
    \(a \leqslant 0.98\)41.45
    \(0.98 < a \leqslant 0.99\)65.23
    \(0.99 < a \leqslant 1.00\)913.98
    \(1.00 < a \leqslant 1.01\)1523.91
    \(1.01 < a \leqslant 1.02\)3726.15
    \(1.02 < a \leqslant 1.03\)2118.29
    \(1.03 < a\)810.99
    Carry out a test at the \(5 \%\) level of significance of the goodness of fit of the Normal model. State your conclusion carefully and comment on your findings.
  2. The forecaster buys a new digital barometer that can be linked to her computer for easier recording of observations. She decides that she wishes to compare the readings of the new barometer with those of the old one. For a random sample of 10 days, the readings (in atmospheres) of the two barometers are shown below.
    DayABCDEFGHIJ
    Old0.9921.0051.0011.0111.0260.9801.0201.0251.0421.009
    New0.9851.0031.0021.0141.0220.9881.0301.0161.0471.025
    Use an appropriate Wilcoxon test to examine at the \(10 \%\) level of significance whether there is any reason to suppose that, on the whole, readings on the old and new barometers do not agree.
OCR MEI S3 2006 June Q1
18 marks Standard +0.3
1 Design engineers are simulating the load on a particular part of a complex structure. They intend that the simulated load, measured in a convenient unit, should be given by the random variable \(X\) having probability density function $$f ( x ) = 12 x ^ { 3 } - 24 x ^ { 2 } + 12 x , \quad 0 \leqslant x \leqslant 1 .$$
  1. Find the mean and the mode of \(X\).
  2. Find the cumulative distribution function \(\mathrm { F } ( x )\) of \(X\). $$\text { Verify that } \mathrm { F } \left( \frac { 1 } { 4 } \right) = \frac { 67 } { 256 } , \mathrm {~F} \left( \frac { 1 } { 2 } \right) = \frac { 11 } { 16 } \text { and } \mathrm { F } \left( \frac { 3 } { 4 } \right) = \frac { 243 } { 256 } .$$ The engineers suspect that the process for generating simulated loads might not be working as intended. To investigate this, they generate a random sample of 512 loads. These are recorded in a frequency distribution as follows.
    Load \(x\)\(0 \leqslant x \leqslant \frac { 1 } { 4 }\)\(\frac { 1 } { 4 } < x \leqslant \frac { 1 } { 2 }\)\(\frac { 1 } { 2 } < x \leqslant \frac { 3 } { 4 }\)\(\frac { 3 } { 4 } < x \leqslant 1\)
    Frequency12620913146
  3. Use a suitable statistical procedure to assess the goodness of fit of \(X\) to these data. Discuss your conclusions briefly.
OCR MEI S3 2006 June Q2
18 marks Standard +0.3
2 A bus route runs from the centre of town A through the town's urban area to a point B on its boundary and then through the country to a small town C . Because of traffic congestion and general road conditions, delays occur on both the urban and the country sections. All delays may be considered independent. The scheduled time for the journey from A to B is 24 minutes. In fact, journey times over this section are given by the Normally distributed random variable \(X\) with mean 26 minutes and standard deviation 3 minutes. The scheduled time for the journey from B to C is 18 minutes. In fact, journey times over this section are given by the Normally distributed random variable \(Y\) with mean 15 minutes and standard deviation 2 minutes. Journey times on the two sections of route may be considered independent. The timetable published to the public does not show details of times at intermediate points; thus, if a bus is running early, it merely continues on its journey and is not required to wait.
  1. Find the probability that a journey from A to B is completed in less than the scheduled time of 24 minutes.
  2. Find the probability that a journey from A to C is completed in less than the scheduled time of 42 minutes.
  3. It is proposed to introduce a system of bus lanes in the urban area. It is believed that this would mean that the journey time from A to B would be given by the random variable \(0.85 X\). Assuming this to be the case, find the probability that a journey from A to B would be completed in less than the currently scheduled time of 24 minutes.
  4. An alternative proposal is to introduce an express service. This would leave out some bus stops on both sections of the route and its overall journey time from A to C would be given by the random variable \(0.9 X + 0.8 Y\). The scheduled time from A to C is to be given as a whole number of minutes. Find the least possible scheduled time such that, with probability 0.75 , buses would complete the journey on time or early.
  5. A programme of minor road improvements is undertaken on the country section. After their completion, it is thought that the random variable giving the journey time from B to C is still Normally distributed with standard deviation 2 minutes. A random sample of 15 journeys is found to have a sample mean journey time from B to C of 13.4 minutes. Provide a two-sided \(95 \%\) confidence interval for the population mean journey time from B to C .
OCR MEI S3 2006 June Q3
18 marks Moderate -0.3
3 An employer has commissioned an opinion polling organisation to undertake a survey of the attitudes of staff to proposed changes in the pension scheme. The staff are categorised as management, professional and administrative, and it is thought that there might be considerable differences of opinion between the categories. There are 60,140 and 300 staff respectively in the categories. The budget for the survey allows for a sample of 40 members of staff to be selected for in-depth interviews.
  1. Explain why it would be unwise to select a simple random sample from all the staff.
  2. Discuss whether it would be sensible to consider systematic sampling.
  3. What are the advantages of stratified sampling in this situation?
  4. State the sample sizes in each category if stratified sampling with as nearly as possible proportional allocation is used. The opinion polling organisation needs to estimate the average wealth of staff in the categories, in terms of property, savings, investments and so on. In a random sample of 11 professional staff, the sample mean is \(\pounds 345818\) and the sample standard deviation is \(\pounds 69241\).
  5. Assuming the underlying population is Normally distributed, test at the \(5 \%\) level of significance the null hypothesis that the population mean is \(\pounds 300000\) against the alternative hypothesis that it is greater than \(\pounds 300000\). Provide also a two-sided \(95 \%\) confidence interval for the population mean.
    [0pt] [10]
OCR MEI S3 2006 June Q4
18 marks Moderate -0.3
4 A company has many factories. It is concerned about incidents of trespassing and, in the hope of reducing if not eliminating these, has embarked on a programme of installing new fencing.
  1. Records for a random sample of 9 factories of the numbers of trespass incidents in typical weeks before and after installation of the new fencing are as follows.
    FactoryABCDEFGHI
    Number before installation81264142241314
    Number after installation6110118101154
    Use a Wilcoxon test to examine at the \(5 \%\) level of significance whether it appears that, on the whole, the number of trespass incidents per week is lower after the installation of the new fencing than before.
  2. Records are also available of the costs of damage from typical trespass incidents before and after the introduction of the new fencing for a random sample of 7 factories, as follows (in £).
    FactoryTUVWXYZ
    Cost before installation1215955464672356236550
    Cost after installation12681105784802417318620
    Stating carefully the required distributional assumption, provide a two-sided \(99 \%\) confidence interval based on a \(t\) distribution for the population mean difference between costs of damage before and after installation of the new fencing. Explain why this confidence interval should not be based on the Normal distribution.
OCR MEI S3 2007 June Q1
18 marks Standard +0.3
1 A manufacturer of fireworks is investigating the lengths of time for which the fireworks burn. For a particular type of firework this length of time, in minutes, is modelled by the random variable \(T\) with probability density function $$\mathrm { f } ( t ) = k t ^ { 3 } ( 2 - t ) \quad \text { for } 0 < t \leqslant 2$$ where \(k\) is a constant.
  1. Show that \(k = \frac { 5 } { 8 }\).
  2. Find the modal time.
  3. Find \(\mathrm { E } ( T )\) and show that \(\operatorname { Var } ( T ) = \frac { 8 } { 63 }\).
  4. A large random sample of \(n\) fireworks of this type is tested. Write down in terms of \(n\) the approximate distribution of \(\bar { T }\), the sample mean time.
  5. For a random sample of 100 such fireworks the times are summarised as follows. $$\Sigma t = 145.2 \quad \Sigma t ^ { 2 } = 223.41$$ Find a 95\% confidence interval for the mean time for this type of firework and hence comment on the appropriateness of the model.
OCR MEI S3 2007 June Q2
18 marks Standard +0.3
2 The operator of a section of motorway toll road records its weekly takings according to the types of vehicles using the motorway. For purposes of charging, there are three types of vehicle: cars, coaches, lorries. The weekly takings (in thousands of pounds) for each type are assumed to be Normally distributed. These distributions are independent of each other and are summarised in the table.
Vehicle typeMeanStandard deviation
Cars60.25.2
Coaches33.96.3
Lorries52.44.9
  1. Find the probability that the weekly takings for coaches are less than \(\pounds 40000\).
  2. Find the probability that the weekly takings for lorries exceed the weekly takings for cars.
  3. Find the probability that over a 4 -week period the total takings for cars exceed \(\pounds 225000\). What assumption must be made about the four weeks?
  4. Each week the operator allocates part of the takings for repairs. This is determined for each type of vehicle according to estimates of the long-term damage caused. It is calculated as follows: \(5 \%\) of takings for cars, \(10 \%\) for coaches and \(20 \%\) for lorries. Find the probability that in any given week the total amount allocated for repairs will exceed \(\pounds 20000\).
OCR MEI S3 2007 June Q3
18 marks Standard +0.3
3 The management of a large chain of shops aims to reduce the level of absenteeism among its workforce by means of an incentive bonus scheme. In order to evaluate the effectiveness of the scheme, the management measures the percentage of working days lost before and after its introduction for each of a random sample of 11 shops. The results are shown below.
ShopABCDEFGHIJK
\% days lost before3.55.03.53.24.54.94.16.06.88.16.0
\% days lost after1.84.32.94.54.45.83.56.76.45.45.1
  1. The management decides to carry out a \(t\) test to investigate whether there has been a reduction in absenteeism.
    1. State clearly the hypotheses that should be used together with any necessary assumptions.
    2. Carry out the test using a \(5 \%\) significance level.
  2. Find a 95\% confidence interval for the true mean percentage of days lost after the introduction of the incentive scheme and state any assumption needed. The management has set a target that the mean percentage should be 3.5. Do you think this has been achieved? Explain your answer.
OCR MEI S3 2007 June Q4
18 marks Standard +0.3
4 A machine produces plastic strip in a continuous process. Occasionally there is a flaw at some point along the strip. The length of strip (in hundreds of metres) between successive flaws is modelled by a continuous random variable \(X\) with probability density function \(\mathrm { f } ( x ) = \frac { 18 } { ( 3 + x ) ^ { 3 } }\) for \(x > 0\). The table below gives the frequencies for 100 randomly chosen observations of \(X\). It also gives the probabilities for the class intervals using the model.
Length \(x\) (hundreds of metres)Observed frequencyProbability
\(0 < x \leqslant 0.5\)210.2653
\(0.5 < x \leqslant 1\)240.1722
\(1 < x \leqslant 2\)120.2025
\(2 < x \leqslant 3\)150.1100
\(3 < x \leqslant 5\)130.1094
\(5 < x \leqslant 10\)90.0874
\(x > 10\)60.0532
  1. Examine the fit of this model to the data at the \(5 \%\) level of significance. You are given that the median length between successive flaws is 124 metres. At a later date the following random sample of ten lengths (in metres) between flaws is obtained. $$\begin{array} { l l l l l l l l l l } 239 & 77 & 179 & 221 & 100 & 312 & 52 & 129 & 236 & 42 \end{array}$$
  2. Test at the \(10 \%\) level of significance whether the median length may still be assumed to be 124 metres.
OCR S3 2014 June Q1
5 marks Standard +0.3
1 The independent random variables \(X\) and \(Y\) have Poisson distributions with parameters 16 and 2 respectively, and \(Z = \frac { 1 } { 2 } X - Y\).
  1. Find \(\mathrm { E } ( Z )\) and \(\operatorname { Var } ( Z )\).
  2. State whether \(Z\) has a Poisson distribution, giving a reason for your answer.
OCR S3 2014 June Q2
6 marks Standard +0.3
2 In a study of the inheritance of skin colouration in corn snakes, a researcher found 865 snakes with black and orange bodies, 320 snakes with black bodies, 335 snakes with orange bodies and 112 snakes with bodies of other colours. Theory predicts that snakes of these colours should occur in the ratios \(9 : 3 : 3 : 1\). Test, at the \(5 \%\) significance level, whether these experimental results are compatible with theory.
OCR S3 2014 June Q3
7 marks Standard +0.3
3 An athlete finds that her times for running 100 m are normally distributed. Before a period of intensive training, her mean time is 11.8 s . After the period of intensive training, five randomly selected times, in seconds, are as follows. $$\begin{array} { l l l l l } 11.70 & 11.65 & 11.80 & 11.75 & 11.60 \end{array}$$ Carry out a suitable test, at the \(5 \%\) significance level, to investigate whether times after the training are less, on average, than times before the training.
OCR S3 2014 June Q4
7 marks Standard +0.3
4 Cola is sold in bottles and cans. The volume of cola in a bottle is normally distributed with mean 500 ml and standard deviation 10 ml . The volume of cola in a can is normally distributed with mean 330 ml and standard deviation 8 ml . Find the probability that the total volume of cola in 2 randomly selected bottles is greater than 3 times the volume of cola in a randomly selected can.
OCR S3 2014 June Q5
9 marks Standard +0.3
5 The day before the 1992 General Election, an opinion poll showed that \(37.6 \%\) of a random sample of 1731 voters intended to vote for the Conservative party.
  1. Calculate an approximate \(99.9 \%\) confidence interval for the proportion of voters intending to vote Conservative. The actual proportion voting Conservative was above the upper limit of the confidence interval.
  2. Give two possible reasons for this occurrence.
  3. What sample size would be required to produce a \(99.9 \%\) confidence interval of width 0.05 ?