Cambridge IGCSE™ Statistics Digital Coursebook (2 Years)
Author/s: Dean Chalmers
Format: Digital
This series supports students through the Cambridge IGCSE™ Statistics syllabus (0479) for examination from 2027.
This digital 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.
Features:
Contents:
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