IB Maths AI HL Topic 4: Statistics and probability questions

Exam-style questions in the shape of Paper 1 and Paper 2, with full markschemes. Read the markscheme, or type, photograph or draw your answer and get it marked.

Question 1

Paper 2Hard6 marks

A city council is estimating the number of potholes on a typical 1 km road segment. It has two samples, each containing 40 segments.

The app sample consists of segments for which residents submitted reports during one month. Reports were grouped by segment, but the counts were not independently checked. The inspection sample was selected by stratified random sampling, in proportion to the number of segments in each road class. Inspectors counted and checked the potholes.

Figure 1 shows box-and-whisker plots of the recorded number of potholes per segment. Inspection confirmed that the segment represented by the value 14 had 14 distinct potholes. The value 18 in the app sample has not been checked.

For this question, a value is an outlier if it is more than 1.5×IQR1.5\times\mathrm{IQR} beyond the nearest quartile.

02468101214161820Recorded potholes per 1 km road segmentApp sampleInspection sample

The council proposes deleting both marked high values as recording errors and using the remaining app sample to estimate the typical number of potholes per city segment.

(a)

For each sample, calculate the upper outlier fence and determine whether its marked high value is an outlier.

[2]
(b)

Using your result from part (a), evaluate the council’s proposal. Recommend a defensible way to estimate the typical number of potholes, using evidence from Figure 1 and the sampling information.

[4]

Question 2

Paper 2Hard6 marks

A parcel depot records the dispatch-to-arrival times, in minutes, for equal samples of 60 deliveries on each of two routes. The summaries below give the whisker endpoints, quartiles and any outliers. The outlier is marked with a cross; there are no other outliers.

RouteLower whiskerQ1Q_1MedianQ3Q_3Upper whiskerOutlier
A12.418.122.026.029.954.2 ×
B15.219.123.027.131.0—
(a)

Calculate the interquartile range for each route. Give your answers in minutes.

[2]
(b)

A supervisor concludes that Route A has more variable delivery times and is less likely to have a normally distributed set of times than Route B. Evaluate this conclusion using the summaries.

[4]

Question 3

Paper 1Hard6 marks

During a greenhouse trial, a horticulturist measures the height of a young plant on days 0 to 5. The measurements, rounded to the nearest centimetre, are shown in Figure 1.

01234505101520253035Elapsed time, x (days)Height, h (cm)(0, 8)(1, 10)(2, 14)(3, 18)(4, 25)(5, 31)
(a)

Use your GDC to fit a quadratic least-squares regression curve to the observations. Give its equation, R2R^2 and SSresSS_{\mathrm{res}}

[2]
(b)

Use your GDC to fit a linear least-squares regression curve to the observations. Give its R2R^2 SSresSS_{\mathrm{res}} and Pearson’s product moment correlation coefficient, rr Show numerically that R2=r2R^2=r^2 for this linear model.

[2]
(c)

A horticulturist claims that the quadratic model must be used to estimate the plant’s height on day 8 because it has the larger R2R^2 Assess this claim using the graph and your results.

[2]

Question 4

Paper 2Medium5 marks

At a parcel centre, XX is the excess handling time, in minutes, for a randomly selected parcel. Figure 1 shows the probability distribution of XX

012300.10.20.30.40.50.6Excess handling time, x (min)P(X=x)0.200.500.30
(a)

Calculate E(X)\mathrm{E}(X) and Var(X)\mathrm{Var}(X)

[3]
(b)

For a parcel with excess handling time XX the additional handling charge YY in AUD, is modelled by Y=3X+2Y=3X+2 Hence determine E(Y)\mathrm{E}(Y) and Var(Y)\mathrm{Var}(Y)

[2]

Question 5

Paper 1Hard6 marks

A local emergency department records two types of admissions during each 20-minute interval. The two streams of admissions are independent, and admissions occur independently at a uniform average rate throughout each interval. The mean numbers are 1.4 type A admissions and 0.9 type B admissions per interval.

A planner is considering a normal, binomial or Poisson model for the total number, NN of admissions in an interval.

(a)

Show that a suitable model for NN is a Poisson distribution with mean 2.3.

[2]
(b)

The department can assess at most CC admissions during an interval. The planner requires the probability that the department can assess all admissions to be at least 0.95.

Using your model from part (a), determine the smallest possible integer value of CC Show numerical evidence that it is the smallest value satisfying the requirement.

[4]

Question 6

Paper 2Hard6 marks

A snack company models the mass, XX g, of a packet as normally distributed with mean 503503 g and standard deviation 4.84.8 g. Packets with mass below 494494 g do not meet the lower specification. The company wants at least 94%94\% of packets to meet the specification 494≤X≤U494\leq X\leq U where UU is the upper specification.

Use your GDC for normal probability and inverse normal calculations.

(a)

Show that P(X<494)=0.0304P(X<494)=0.0304

[2]
(b)

Using your result from part (a), determine the smallest value of UU to the nearest 0.10.1 g, that meets the company’s requirement. A manager proposes setting UU to the 95th percentile of the distribution. Assess whether this proposal meets the requirement.

[4]

Question 7

Paper 1Medium6 marks

A parcel-delivery company defines its daily forecast error as

actual number of parcels−forecast number of parcels.\text{actual number of parcels}-\text{forecast number of parcels}.

A random sample of 16 independent days has a mean forecast error of 18.4 parcels and a sample standard deviation of 12.0 parcels. The daily forecast errors may be modelled by a normal population, whose standard deviation is unknown.

(a)

State which distribution should be used to construct a confidence interval for the population mean forecast error, μ\mu

[1]
(b)

Calculate a 95% confidence interval for μ\mu Give both endpoints to one decimal place.

[3]
(c)

The planning director claims that the forecasts are unbiased, so that μ=0\mu=0 Use your interval to comment on this claim and state the direction of any bias indicated.

[2]

Question 8

Paper 1Hard6 marks

A field team measures the nitrate concentration in water samples from a catchment. The eight samples are selected independently at random. Assume that the population of nitrate concentrations is normally distributed, with known standard deviation 1.2 mg L−11.2\text{ mg L}^{-1}

Figure 1 shows the measured concentrations. The team will test whether the population mean concentration exceeds 5.0 mg L−15.0\text{ mg L}^{-1} using

H0:μ=5.0,H1:μ>5.0,H_0:\mu=5.0,\qquad H_1:\mu>5.0,

where μ\mu is measured in mg L−1\text{mg L}^{-1}

012345678944.555.566.57Sample numberNitrate concentration (mg L⁻¹)4.14.75.25.45.86.16.36.8
(a)

Use Figure 1 to determine the sample mean concentration.

[1]
(b)

Using your answer to part (a), carry out the stated test at the 5% significance level. State your conclusion in context.

[2]
(c)

Suppose that the true population mean concentration is 5.8 mg L−15.8\text{ mg L}^{-1} Determine the probability of a Type II error for the test in part (b). Give your answer to three significant figures.

[3]

Question 9

Paper 1Hard6 marks

During fieldwork, students randomly selected 50 plots in each of three habitat types and recorded whether a particular plant species was present.

Habitat typePlant presentPlant absent
Woodland interior2228
Woodland edge3515
Open scrub2327
(a)

State appropriate null and alternative hypotheses for investigating whether plant presence is related to habitat type.

[2]
(b)

Using an appropriate statistical test and your GDC, determine the test statistic, its degrees of freedom and the p-value.

[2]
(c)

At the 5% significance level, state what the data indicate. A volunteer claims that the test proves woodland edge causes a greater probability of plant presence than open scrub. Assess this claim.

[2]

Question 10

Paper 1Hard6 marks

A rail authority models the monthly change in commuters’ usual station between North (N) and South (S). The state matrix is a column matrix, with entries giving the proportions using N and S, in that order. The transition matrix is

T=(0.80.30.20.7),T=\begin{pmatrix}0.8&0.3\\0.2&0.7\end{pmatrix},

where rows represent the station used in the next month and columns represent the station used in the current month. Initially,

s0=(0.100.90).s_0=\begin{pmatrix}0.10\\0.90\end{pmatrix}.
(a)

Calculate s1s_1

[1]
(b)

Find the least whole number of months n≥1n\geq 1 for which the proportion using N is within 0.010.01 of its long-term proportion. Justify why this condition holds for every subsequent month.

[5]

Question 11

Paper 1Hard6 marks

A university models changes in students’ preferred meal-collection hub (A, B or C) from one month to the next. The columns of the transition matrix TT represent the current hub, and the rows represent the hub in the following month. The state matrices are column matrices.

T=(0.60.20.1x0.50.20.4−x0.30.7)T= \begin{pmatrix} 0.6&0.2&0.1\\ x&0.5&0.2\\ 0.4-x&0.3&0.7 \end{pmatrix}

The initial state matrix and the state matrix one month later are

s0=(0.500.300.20),s1=(0.380.340.28).s_0= \begin{pmatrix} 0.50\\ 0.30\\ 0.20 \end{pmatrix}, \qquad s_1= \begin{pmatrix} 0.38\\ 0.34\\ 0.28 \end{pmatrix}.

The same transition matrix applies each month, and the resulting Markov chain is regular.

(a)

Determine the value of xx

[2]
(b)

A manager claims that more than half of the students will use hub C in the long term because 0.70.7 of the students currently using C remain there the following month.

Determine the long-term proportions of students using each hub and decide whether the manager’s claim is correct. Give the proportions to three significant figures.

[4]

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