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IBDP Maths AI HL Predicted Paper 3 sample

Questions

Question 1

A showroom sells cars in five price ranges over one year. A frequency density histogram (with unequal class widths) summarises the data. It is given that 66 cars in the price range £10 000–£20 000 were sold.

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Part a
[3]

Explain why the bar for £10 000–£20 000 must have frequency density 0.00660.0066 (cars per £). Hence, state the scale of the vertical axis to 44 d.p.

Part b
[3]

Let the frequency densities of the remaining classes, in order of increasing price, be h2h_2, h3h_3, h4h_4, h5h_5 (cars per £).
Write an expression for the total number of cars NN sold in the year in terms of h2h_2, h3h_3, h4h_4, h5h_5. State the class widths you used.

Part c
[6]

By reading the histogram carefully (use the tick marks and grid), estimate the heights h2h_2, h3h_3, h4h_4, h5h_5 to the nearest 0.00010.0001. Hence estimate the number of cars sold in each class and the total NN.

Part d
[4]

Use your class frequencies to estimate the median price of a car sold. Use linear interpolation within the relevant class and show your working.

Part e
[6]

For price pp (in £) with p10,000p \ge 10,000, assume the frequency density f(p)f(p) (cars per £) decays exponentially: f(p)=Aekpf(p)=A e^{kp}, with k<0k<0.
Using the point at the centre of the first full-width bar and the point at the centre of the final (long) bar (read these from the histogram), determine AA and kk, giving each to 33 s.f. Comment on the appropriateness of this model for the middle price classes.

Part f
[5]

A manager states: “At least 2525% of cars sold cost more than £40 000.”
Use your histogram-based calculations to assess this claim, giving a justified conclusion.

[27]

Question 2

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