HL AI · Number and Algebra
Updated October 2026
Quick answer: An exponential decay model is y = a e−kt (or y = a bᵗ with 0 < b < 1). Taking natural logs gives ln y = ln a − kt, a straight line in t. So to fit the model to data, find the regression line of ln y on t: its gradient is −k and its intercept is ln a. The half-life is ln 2 ÷ k.
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Practise HL AI Number and Algebra →A cup of tea cools in a room at 20°C. The excess temperature y = T − 20 (°C) is recorded: t = 0, 10, 20, 30 minutes gives y = 60, 36.4, 22.1, 13.4. Fit a model y = a e−kt using ln y, find the time for the excess temperature to halve, and estimate T after 40 minutes.
Answer: y = 60.0 e−0.0500t; the excess temperature halves every 13.9 minutes; T ≈ 28.1°C after 40 minutes.
The table shows the number of bacteria (in thousands) after x hours. Change a and b so that y = a·bˣ fits the data (the check wants R² of at least 0.99). What do a and b mean in this context?
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5 quick questions on depreciation. No sign-in needed.
A GDC is allowed on every AI paper. Keystrokes for the TI-84 Plus CE, TI-Nspire CX II and Casio fx-CG50, with a checked worked example:
Stretch yourself: original algebra problems at Senior level (ages 16 to 18), with hints and full solutions: Problem S22 · Problem S86 · Problem S93 · Problem S28. All 22 →
Take the natural log of each y-value and find the linear regression line of ln y against t. The gradient is −k and the intercept is ln a, so the model is y = e^(intercept) × e^(gradient × t). The GDC's exponential regression does the same in one step.
Yes: a GDC is allowed on every HL AI paper, so practise the calculator method as well as the working. The Regression guide gives the keystrokes for the TI-84 Plus CE, TI-Nspire CX II and Casio fx-CG50.
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