Questions — OCR (4907 questions)

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OCR S3 2007 June Q2
7 marks Moderate -0.3
2 Two brands of car battery, 'Invincible' and 'Excelsior', have lifetimes which are normally distributed. Invincible batteries have a mean lifetime of 5 years with standard deviation 0.7 years. Excelsior batteries have a mean lifetime of 4.5 years with standard deviation 0.5 years. Random samples of 20 Invincible batteries and 25 Excelsior batteries are selected and the sample mean lifetimes are \(\bar { X } _ { I }\) years and \(\bar { X } _ { E }\) years respectively.
  1. State the distributions of \(\bar { X } _ { I }\) and \(\bar { X } _ { E }\).
  2. Calculate \(\mathrm { P } \left( \bar { X } _ { I } - \bar { X } _ { E } \geqslant 1 \right)\).
OCR S3 2007 June Q3
8 marks Standard +0.3
3 A nurse was asked to measure the blood pressure of 12 patients using an aneroid device. The nurse's readings were immediately checked using an accurate electronic device. The differences, \(x\), given by \(x =\) (aneroid reading - electronic reading), in appropriate units, are shown below. $$\begin{array} { c c c c c c c c c c c } - 1.3 & 4.7 & - 0.9 & 3.8 & - 1.5 & 4.0 & - 1.9 & 4.4 & - 0.8 & 5.5 & - 2.9 \end{array} 4.1$$ Stating any assumption you need to make, test, at the \(10 \%\) significance level, whether readings with an aneroid device, on average, overestimate patients' blood pressure.
OCR S3 2007 June Q4
9 marks Standard +0.3
4 The students in a large university department take a trial examination some time before the proper examination. A random sample of 60 students took both examinations during a particular course. 42 students passed the trial examination, 36 passed the proper examination and 13 failed both examinations.
  1. Copy and complete the following contingency table.
    Proper
    \cline { 2 - 4 } \multicolumn{1}{l}{}PassFailTotal
    \cline { 2 - 5 }Pass42
    \cline { 2 - 5 } TrialFail13
    \cline { 2 - 5 }Total3660
  2. Carry out a test of independence at the \(\frac { 1 } { 2 } \%\) level of significance.
OCR S3 2007 June Q5
9 marks Standard +0.3
5 A music store sells both upright and grand pianos. Grand pianos are sold at random times and at a constant average weekly rate \(\lambda\). The probability that in one week no grand pianos are sold is 0.45 .
  1. Show that \(\lambda = 0.80\), correct to 2 decimal places. Upright pianos are sold, independently, at random times and at a constant average weekly rate \(\mu\). During a period of 100 weeks the store sold 180 upright pianos.
  2. Calculate the probability that the total number of pianos sold in a randomly chosen week will exceed 3.
  3. Calculate the probability that over a period of 3 weeks the store sells a total of 6 pianos during the first week and a total of 4 pianos during the next fortnight.
OCR S3 2007 June Q6
12 marks Standard +0.3
6 Random samples of 200 'Alpha' and 150 'Beta' vacuum cleaners were monitored for reliability. It was found that 62 Alpha and 35 Beta cleaners required repair during the guarantee period of one year. The proportions of all Alpha and Beta cleaners that require repair during the guarantee period are \(p _ { \alpha }\) and \(p _ { \beta }\) respectively.
  1. Find a \(95 \%\) confidence interval for \(p _ { \alpha }\).
  2. Give a reason why, apart from rounding, the interval is approximate.
  3. Test, at the \(5 \%\) significance level, whether \(p _ { \alpha }\) differs from \(p _ { \beta }\).
OCR S3 2007 June Q7
9 marks Challenging +1.2
7 The continuous random variable \(X\) has (cumulative) distribution function given by $$\mathrm { F } ( x ) = \begin{cases} 0 & x < 1 \\ 1 - \frac { 1 } { x ^ { 4 } } & x \geqslant 1 \end{cases}$$
  1. Find the (cumulative) distribution function, \(\mathrm { G } ( y )\), of the random variable \(Y\), where \(Y = \frac { 1 } { X ^ { 2 } }\).
  2. Hence show that the probability density function of \(Y\) is given by $$g ( y ) = \begin{cases} 2 y & 0 < y \leqslant 1 \\ 0 & \text { otherwise } \end{cases}$$
  3. Find \(\mathrm { E } ( \sqrt [ 3 ] { Y } )\).
OCR S3 2007 June Q8
14 marks Standard +0.3
8 The continuous random variable \(Y\) has a distribution with mean \(\mu\) and variance 20. A random sample of 50 observations of \(Y\) is selected and these observations are summarised in the following grouped frequency table.
Values\(y < 20\)\(20 \leqslant y < 25\)\(25 \leqslant y < 30\)\(y \geqslant 30\)
Frequency327128
  1. Assuming that \(Y \sim \mathrm {~N} ( 25,20 )\), show that the expected frequency for the interval \(20 \leqslant y < 25\) is 18.41, correct to 2 decimal places, and obtain the remaining expected frequencies.
  2. Test, at the \(5 \%\) significance level, whether the distribution \(\mathrm { N } ( 25,20 )\) fits the data.
  3. Given that the sample mean is 24.91 , find a \(98 \%\) confidence interval for \(\mu\).
  4. Does the outcome of the test in part (ii) affect the validity of the confidence interval found in part (iii)? Justify your answer.
OCR S3 2011 June Q1
7 marks Moderate -0.8
1 The random variables \(X\) and \(Y\) are independent with \(X \sim \operatorname { Po } ( 5 )\) and \(Y \sim \operatorname { Po } ( 4 )\). \(S\) denotes the sum of 2 observations of \(X\) and 3 observations of \(Y\).
  1. Find \(\mathrm { E } ( S )\) and \(\operatorname { Var } ( S )\).
  2. The random variable \(T\) is defined by \(\frac { 1 } { 2 } X - \frac { 1 } { 4 } Y\). Show that \(\mathrm { E } ( T ) = \operatorname { Var } ( T )\).
  3. State which of \(S\) and \(T\) (if either) does not have a Poisson distribution, giving a reason for your answer.
OCR S3 2011 June Q2
8 marks Standard +0.3
2 The population proportion of all men with red-green colour blindness is denoted by \(p\). Each of a random sample of 80 men was tested and it was found that 6 had red-green colour blindness.
  1. Calculate an approximate \(95 \%\) confidence interval for \(p\).
  2. For a different random sample of men, the proportion with red-green colour blindness is denoted by \(p _ { s }\). Estimate the sample size required in order that \(\left| p _ { s } - p \right| \leqslant 0.05\) with probability \(95 \%\).
  3. Give one reason why the calculated sample size is an estimate.
OCR S3 2011 June Q3
9 marks Moderate -0.3
3 The monthly demand for a product, \(X\) thousand units, is modelled by the random variable \(X\) with probability density function given by $$f ( x ) = \begin{cases} a x & 0 \leqslant x \leqslant 1 \\ a ( x - 2 ) ^ { 2 } & 1 < x \leqslant 2 \\ 0 & \text { otherwise } \end{cases}$$ where \(a\) is a positive constant. Find
  1. the value of \(a\),
  2. the probability that the monthly demand is at most 1500 units,
  3. the expected monthly demand.
OCR S3 2011 June Q4
9 marks Standard +0.3
4 An experiment by Lord Rutherford at Cambridge in 1909 involved measuring the numbers of \(\alpha\)-particles emitted during radioactive decay. The following table shows emissions during 2608 intervals of 7.5 seconds.
Number of particles emitted, \(x\)012345678910\(\geqslant 11\)
Frequency572033835255324082731394527106
It is given that the mean number of particles emitted per interval, calculated from the data, is 3.87 , correct to 3 significant figures.
  1. Find the contribution to the \(\chi ^ { 2 }\) value of the frequency of 273 corresponding to \(x = 6\) in a goodness of fit test for a Poisson distribution.
  2. Given that no cells need to be combined, state why the number of degrees of freedom is 10 .
  3. Given also that the calculated value of \(\chi ^ { 2 }\) is 13.0 , correct to 3 significant figures, carry out the test at the 10\% significance level.
OCR S3 2011 June Q5
11 marks Standard +0.8
5 The continuous random variable \(X\) has (cumulative) distribution function given by $$\mathrm { F } ( x ) = \begin{cases} 0 & x < 1 , \\ \frac { 4 } { 3 } \left( 1 - \frac { 1 } { x ^ { 2 } } \right) & 1 \leqslant x \leqslant 2 , \\ 1 & x > 2 . \end{cases}$$
  1. Find the median value of \(X\).
  2. Find the (cumulative) distribution function of \(Y\), where \(Y = \frac { 1 } { X ^ { 2 } }\), and hence find the probability density function of \(Y\).
  3. Evaluate \(\mathrm { E } \left( 2 - \frac { 2 } { X ^ { 2 } } \right)\).
OCR S3 2011 June Q6
13 marks Standard +0.3
6 The Body Mass Index (BMI) of each of a random sample of 100 army recruits from a large intake in 2008 was measured. The results are summarised by $$\Sigma x = 2605.0 , \quad \Sigma x ^ { 2 } = 68636.41 .$$ It may be assumed that BMI has a normal distribution.
  1. Find a 98\% confidence interval for the mean BMI of all recruits in 2008.
  2. Estimate the percentage of the intake with a BMI greater than 30.0.
  3. The BMIs of two randomly chosen recruits are denoted by \(\boldsymbol { B } _ { 1 }\) and \(\boldsymbol { B } _ { 2 }\). Estimate \(\mathrm { P } \left( \boldsymbol { B } _ { 1 } - \boldsymbol { B } _ { 2 } < 5 \right)\).
  4. State, giving a reason, for which of the above calculations the normality assumption is unnecessary.
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 S4 2007 June Q1
6 marks Standard +0.3
1 For the events \(A\) and \(B , \mathrm { P } ( A ) = 0.3 , \mathrm { P } ( B ) = 0.6\) and \(\mathrm { P } \left( A ^ { \prime } \cap B ^ { \prime } \right) = c\), where \(c \neq 0\).
  1. Find \(\mathrm { P } ( A \cap B )\) in terms of \(c\).
  2. Find \(\mathrm { P } ( B \mid A )\) and deduce that \(0.1 \leqslant c \leqslant 0.4\).
OCR S4 2007 June Q2
7 marks Standard +0.3
2 Of 9 randomly chosen students attending a lecture, 4 were found to be smokers and 5 were nonsmokers. During the lecture their pulse-rates were measured, with the following results in beats per minute.
Smokers77859098
Non-smokers5964688088
It may be assumed that these two groups of students were random samples from the student populations of smokers and non-smokers. Using a suitable Wilcoxon test at the \(10 \%\) significance level, test whether there is a difference in the median pulse-rates of the two populations.
OCR S4 2007 June Q3
7 marks Standard +0.3
3 The discrete random variables \(X\) and \(Y\) have the joint probability distribution given in the following table.
\(X\)
\cline { 2 - 5 } \multicolumn{1}{l}{}- 101
10.240.220.04
20.260.180.06
  1. Show that \(\operatorname { Cov } ( X , Y ) = 0\).
  2. Find the conditional distribution of \(X\) given that \(Y = 2\).
OCR S4 2007 June Q4
10 marks Standard +0.3
4 The levels of impurity in a particular alloy were measured using a random sample of 20 specimens. The results, in suitable units, were as follows.
3.002.053.152.653.503.252.853.352.652.75
2.902.202.953.053.653.452.552.152.802.60
  1. Use the sign test, at the \(5 \%\) significance level, to decide if there is evidence that the population median level of impurity is greater than 2.70 .
  2. State what other test might have been used, and give one advantage and one disadvantage this other test has over the sign test.