Product Description
Cambridge IGCSE™ Statistics Coursebook with Digital Access (2 Years)
Author(s): Dean Chalmers
Format: Digital
Format: Print + Digital bundle This series supports students through the Cambridge IGCSE™ Statistics syllabus (0479) for examination from 2027. This coursebook will help 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.
Students are prepared 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
Features:
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Varied exercises throughout each unit encourage students to practise key skills in real-life contexts.
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Worked examples demonstrate the process of a specific task and provide examples of data interpretation, offering an ideal problem-solving structure to support students.
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Investigation tasks enable students to further enhance their knowledge by exploring key concepts in more depth.
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'Discussion' feature encourages students to talk about what they have learnt and consider different techniques and interpretations of statistics.
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'Self-assessment' feature encourages students to think about how they have approached each task and consider their level of understanding.
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'Reflection' feature helps students consolidate their learning and consider how they could improve further.
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Self-evaluation checklists, with 'I am able to' statements linked to the learning intentions, help students review their knowledge.
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Support for English as a second language (ESL) learners with highlighted key words, supporting illustrations, and a clear language of instruction.
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Additional support for planning and teaching with the 'Getting started' feature, which helps you assess what students already know about each topic and identify any learning gaps.
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Useful formula is highlighted next to exercises where it may be used to aid calculations and tips are included to guide students through key topics.
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Accessibility Information: This publication meets the requirements of the EPUB Accessibility specification with conformance to WCAG 2.2 Level AA.
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