pptx, 2.4 MB
pptx, 2.4 MB

IB Math AI SL 4.8 – Binomial Distribution

This lesson introduces students to the binomial distribution, one of the most important discrete probability models in statistics. Students learn that a binomial distribution models the number of “successes” in a fixed number of independent trials, where each trial has only two possible outcomes and a constant probability of success.

The presentation develops both the conceptual understanding and mathematical formulation of the distribution, showing how to calculate the probability of r successes, the expected value (mean), and the variance. Step-by-step proofs and worked examples guide students through the reasoning behind the formulas ( E(X) = np ) and ( Var(X) = np(1-p) ). Practice problems, such as modeling a basketball player’s free throws or testing product reliability, illustrate the real-world applications of the distribution. The lesson also emphasizes the assumptions underlying the model—fixed number of trials, independence, and constant probability—and shows how violations affect accuracy.

By the end of the lesson, students can model random processes using binomial distributions, calculate probabilities, and interpret expected outcomes and variability. Fully aligned with IB Math AI SL Topic 4.8 – Binomial Distribution, this slide deck builds a strong foundation for later topics in inferential statistics and probability-based modelling.

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IB Math AI Unit 4 - Statistics Slidedeck Bundle

**IB Math AI & HL Unit 4 – Statistics Bundle** **Topics:** Covers all Topic 4 sub-topics from SL and HL, ranging from data presentation and measures of spread, through correlation, regression, discrete and continuous distributions, to hypothesis testing and parametric models. **Level:** IB Mathematics: Applications & Interpretation (SL) and Higher Level (HL) **File Type:** Complete editable slide deck bundle **Bundle Price:** £40 (save 30 % compared to individual purchase) --- ### **Overview** This comprehensive bundle brings together all the slide decks your students need to master the entire **Statistics & Probability Unit (Topic 4)** of the IB Mathematics AI/HL curriculum. From collecting and describing data, to modelling with binomial, normal and Poisson distributions, and completing full hypothesis tests, each lesson is structured to build conceptual understanding and procedural fluency. The decks seamlessly integrate technology use, exam-style reasoning and real-world applications to prepare learners for both SL and HL assessments. --- ### **Learning Outcomes** By the end of the bundle, students will be able to: * Present data using frequency tables, histograms, box-and-whisker plots and cumulative graphs. * Compute and interpret measures of central tendency and spread (mean, median, mode, IQR, standard deviation). * Construct scatter plots, calculate correlation coefficients (Pearson and Spearman) and regression lines, and interpret them in context. * Use discrete models (binomial, Poisson), continuous models (normal), perform standardisation and inverse calculations, and understand expected value and variance. * Understand hypothesis testing frameworks: setting null/alternative hypotheses, using critical regions or p-values, and interpreting Type I and Type II errors. * Design valid data collection methods, choose appropriate categorisations for χ²-tests, and apply technology to compute test statistics. --- ### **What’s Included** * Fully editable PowerPoint slide decks for every subsection of Unit 4 in the IB Math AI syllabus * Complete walkthroughs for each sub-topic with definitions, animations, worked examples and technology integration. * Real-world case studies and context-rich problems that match IB assessment style. * Instruction on using calculators/software for distributions, inverse calculations and hypothesis tests. * Ti-nspire calculator demos! * Flexible teaching tools suited for SL, HL and mixed-level classes. --- ### **Why You’ll Love It** * Full coverage of **Topic 4: Statistics & Probability**, which carries approximately 36 teaching hours at SL and 52 hours at HL. ([Richmond County Schools][2]) * Seamless progression from basic data handling to advanced inferential statistics. * Reduction in planning time: everything ready-to-go and fully editable. * Strong alignment with the IB syllabus framework, making classroom delivery and revision structured and coherent. * Excellent value—30 % reduction on individual slide deck pricing, delivering substantial savings for full-unit coverage. --- ### **Tags** IB Math AI SL, IB Math AI HL, Unit 4, Statistics, Probability, Descriptive Statistics, Correlation, Regression, Binomial Distribution, Normal Distribution, Hypothesis Testing, Editable Slides, Classroom Resources, IB Curriculum.

£40.00

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