Written by experienced IB workshop leaders and curriculum developers, this book covers all the course content and essential practice needed for success in the Statistics Option for Higher Level. Enabling a truly IB approach to mathematics, real-world context is thoroughly blended with mathematical applications, supporting deep understanding and instilling confident mathematical thinking skills. Exam support is integrated, building assessment potential.
*Directly linked to the Oxford Higher Level Course Book, naturally extending learning *Drive a truly IB approach to mathematics, helping learners connect mathematical theory with the world around them *The most comprehensive, accurately matched to the most recent syllabus, written by experienced workshop leaders *Build essential mathematical skills with extensive practice enabling confident skills-development *Cement assessment potential, with examiner guidance and exam questions driving confidence in every topic *Complete worked solutions included free online About the series: The only DP resources developed directly with the IB, the Oxford IB Course Books are the most comprehensive core resources to support learners through their study. Fully incorporating the learner profile, resources are assessed by consulting experts in international-mindedness and TOK to ensure these crucial components are deeply embedded into learning.
1. Exploring further probability distributions ; 1.1 Cumulative distribution function ; 1.2 Other probability distributions ; 1.3 Probability generating functions ; 2. Expectation algebra and central limit theorem ; 2.1 Expectation algebra ; 2.2 Sampling distribution of the mean ; 2.3 The central limit theorem ; 3. Exploring statistical analysis methods ; 3.1 Estimators and estimates ; 3.2 Unbiased estimators for the mean and variance of a normal random variable ; 3.3 Confidence intervals for the mean ; 3.4 Hypothesis testing ; 3.5 Type I and Type II errors ; 4. Bivariate distributions ; 4.1 Correlation ; 4.2 Covariance ; 4.3 Hypothesis testing ; 4.4 Linear regression ; 5. Answers
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