Cambridge IGCSE™ Statistics Coursebook with Digital Access (2 Years) (Cambridge International Igcse)

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Cambridge IGCSE™ Statistics Coursebook with Digital Access (2 Years) (Cambridge International Igcse)

Chalmers, Dean

ウェブストア価格 ¥9,220（本体¥8,382）
Cambridge University Press（2025/02発売）
外貨定価 US$ 43.95
ポイント 83pt

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ページ数 412 p.
言語 ENG
商品コード 9781009532402
DDC分類 519.5

Full Description

This coursebook will help your students build a confident working knowledge of concepts in probability and statistics. Students will develop their data literacy skills by using statistics in real-world contexts and analysing the results of statistical techniques. A wide range of activities provide opportunities to practise applying key statistical methods and measures, such as sampling, linear interpolation and standard deviation. Help your students prepare for further study by providing opportunities to display their practical skills, such as selecting an appropriate statistics technique for a given scenario. Suitable to support the Cambridge IGCSE™ Statistics syllabus (0479) for examination from 2027.

Introduction; Chapter 1 Data and its Collection;1.1 Types of data and variable; 1.2 Surveys; 1.3 Types of Sample; Chapter 2 Basic Probability; 2.1 Experiments, Outcomes and Events; Chapter 3 Frequency Distributions of Ungrouped Data; 3.1 Tabular representation; 3.2 Pictorial Representation; 3.3 Venn diagrams; Practice Questions; Chapter 4 Frequency Distributions of Grouped Data; 4.1 Grouped Discrete Data; 4.2 Continuous Data; 4.3 Pictorial representations; Chapter 5 Measures of Central Tendency; 5.1 Measures for Ungrouped Data; 5.2 Measures for Grouped Data; 5.3 Features of the Measures of Central Tendency; Chapter 6 Weighted Averages; 6.1 Weighted means; 6.2 Index Numbers; 6.3 Crude and Standardised rates; Practice Questions; Chapter 7 Measures of Dispersion; 7.1 Range; 7.2 Interquartile Range; 7.3 Linear Interpolation from a Cumulative Frequency Table; 7.4 Standard Deviation and Variance; 7.5 Features of the Measures of Dispersion; Chapter 8 Transformation of Data Sets; 8.1 Derived Distributions; 8.2 Scaling; Chapter 9 Probability and Probability Distributions; 9.1 Mutually Exclusive Events; 9.2 Independent events; 9.3 Conditional probabilities; 9.4 Dependent events; 9.5 Probability distributions and Expectation; Practice Questions; Chapter 10 Bivariate Data; 10.1 Correlation and Scatter Diagrams; 10.2 Lines of best fit; Chapter 11 Time Series; 11.1 Variation and Trend in a time series; 11.2 Seasonal Variation, trend line and moving averages; 11.3 Seasonal Adjustment; Practice Questions; Answers to Exercises and Practice Questions; Glossary; Index