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Last updated

10 February 2026

pdf, 184.83 KB
pdf, 184.83 KB

This IB Math AI HL 4.17 – The Poisson Distribution resource develops students’ understanding of how random events occurring over time or space can be modelled using the Poisson distribution. Students learn the assumptions behind a Poisson model, the probability formula, and the meaning of the parameter λ as the expected number of events in a fixed interval. The material connects probability calculations to real contexts such as arrivals, defects, and rare events, while reinforcing the key properties that the mean and variance are both equal to λ.

Structured tasks guide learners through computing Poisson probabilities, interpreting λ in different time intervals, and modelling totals using the rule for sums of independent Poisson variables. Extended and exam-style problems develop higher-level reasoning about Poisson approximations to binomial models, checking when model assumptions may fail, and applying the distribution in realistic scenarios. With applied contexts and a full answer key, this resource supports HL teaching, IA preparation, and deeper understanding of discrete probability modelling in line with IB Mathematics AI expectations.

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IB Math AI Unit 4 Worksheet Bundle - All Sections Included!

This **IB Mathematics AI Unit 4 – Statistics Bundle** provides a complete set of structured worksheets covering the full statistics strand of the IB Math Applications & Interpretation course. The materials guide students from foundational statistical concepts through interpretation, analysis, and critical evaluation of data, building both procedural fluency and conceptual understanding required for IB assessments. Across the bundle, students work with data collection methods, sampling techniques, measures of central tendency and spread, representation of data, correlation and regression, probability distributions, and hypothesis testing. Tasks are sequenced to move from skill-building exercises to exam-style and extended-response problems, helping learners connect statistical calculations to interpretation in real-world contexts. Emphasis is placed on understanding assumptions, identifying bias and limitations, and interpreting results in context, all key expectations of the AI course. Each worksheet follows a consistent layout and structure to support classroom use, homework, revision, and independent study. Clear scaffolding, varied question styles, and challenge problems develop higher-order reasoning alongside core techniques. A full answer key is included for every worksheet, making this bundle ideal for teachers delivering the Unit 4 statistics syllabus or students preparing for internal and external IB assessments.

£40.00

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