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IB Mathematics: Applications and Interpretation HL · AHL 8: Statistics 2 · AHL 8.3
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Paper 3 modelling: a logistic model Problem set B
One investigation in six questions. Each question gives the values it needs, so you can start anywhere. Keep unrounded values on your calculator, and give answers to 3 significant figures unless told otherwise.
Each question matches the question with the same number in set A. Do the ones you got wrong there.
Difficulty: first skills applying them stretch
Fit the model
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The number of registered members of a city's bike-share scheme, N thousand, is recorded at the end of each year. The time t is in years since the start of 2019, so t = 1 is the end of 2019. The number is modelled by \(N=\dfrac{64}{1+Ce^{-kt}}\), where C and k are positive constants. The table gives the data.
- (a) In context, explain what the value 64 means in the model.
- (b) Use the value of N at t = 2 to show that \(C=15e^{2k}\).
- (c) Use the value of N at t = 7 to find a second expression for C.
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In the model \(N=\dfrac{64}{1+Ce^{-kt}}\), the two data points at t = 2 and t = 7 give \(C=15e^{2k}\) and \(C=0.6e^{7k}\). Use a calculator to solve for k, and keep the unrounded value for later.
- (a) Use your two expressions for C to find the value of k.
- (b) Find the value of C.
Judge the model
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The model is \(N=\dfrac{64}{1+Ce^{-kt}}\) with C = 54.4 and k = 0.644 (keep the unrounded values from your calculator). The model's predictions for t = 3 to 6 are compared with the data, to 1 decimal place. One prediction is missing.
- (a) Calculate the value of a, the value the model gives at t = 5, correct to 1 decimal place.
- (b) Using the value of a to 1 decimal place, find \(SS_{res}\) for the model's predictions.
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The city will use the model if E < 0.35, where \(E=\sqrt{SS_{res}/n}\) and n is the number of predictions made. In the previous question, \(SS_{res}=0.35\) for the n = 4 predictions.
- (a) By finding the value of E, show that the model will be used.
Use the model
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The model is \(N=\dfrac{64}{1+Ce^{-kt}}\) with C = 54.4 and k = 0.644 (keep the unrounded values). N is in thousands of members. The city estimates that 22% of members ride on any one day, and that one bike is needed for every 5 daily riders.
- (a) Use the model to predict the number of members at the end of 2034.
- (b) Use the model to find an expression for the number of bikes, R, needed at time t.
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The number of bikes needed at time t is \(R=\dfrac{2816}{1+54.4e^{-0.644t}}\), using the model for the number of registered members.
- (a) At the end of 2023 the scheme had 1100 bikes, and at the end of 2025 it had 1700. Find the average number of bikes added per year between the end of 2023 and the end of 2025.
- (b) Assume the number of bikes keeps increasing linearly at the rate you found in part (a). Find the value of t, where t ≥ 5, at which the number of bikes first becomes insufficient for the number of daily riders, and hence the year in which this happens.
jmaths.xyz · AI HL · AHL 8.3 Paper 3 modelling: a logistic investigation