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Chapter 6 : Data Handling

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Sections

  • 1

    Data Collection & Organization

    This section introduces data collection and organization, emphasizing different data types and methods for structuring data effectively.

    Learning Practice

  • 1.1

    Data Types

    This section introduces various data types, highlighting their organization and representation methods.

    Learning Practice

  • 1.2

    Activity

    The section covers data handling activities aimed at understanding data collection, representation, and analysis.

    Learning Practice

  • 2

    Data Representation

    Data representation encompasses various methods to visualize and compare data effectively, aiding in analysis and understanding.

    Learning Practice

  • 2.1

    Graphical Methods

    Graphical methods are techniques used to visually represent data, facilitating comparison and understanding.

    Learning Practice

  • 3

    Data Analysis

    This section focuses on how data is analyzed using statistical measures such as mean, median, and mode.

    Learning Practice

  • 3.1

    Statistical Measures

    Statistical measures, including mean, median, and mode, are essential for analyzing and interpreting data effectively.

    Learning Practice

  • 3.2

    Real-World Application

    This section explores how data handling techniques are applied in real-world scenarios like sports analysis and election polling.

    Learning Practice

  • 4

    Probability Basics

    This section introduces the fundamental concepts of probability, including definitions and applications.

    Learning Practice

  • 4.1

    Probability Scale

    The probability scale illustrates the likelihood of an event happening, ranging from impossible to certain.

    Learning Practice

  • 4.2

    Simple Probability

    This section introduces the basics of simple probability, including how to calculate the chance of an event occurring using fundamental concepts.

    Learning Practice

  • 4.3

    Case Study

    This section presents a case study on election poll analysis, emphasizing the processes involved in data collection, representation, and analysis.

    Learning Practice

  • 4.4

    Mathematics Behind

    The 'Mathematics Behind' section focuses on understanding the mathematical principles that underpin data handling, including sample size determination and confidence intervals.

    Learning Practice

  • 5

    Chapter Summary

    This section summarizes the key concepts of data handling, including data collection, representation, analysis, and the basics of probability.

    Learning Practice

  • 6

    Activities

    This section emphasizes engaging activities to deepen understanding of data handling concepts through practical applications.

    Learning Practice

  • 6.1

    School Project

    This section discusses data handling techniques, including data collection, representation, analysis, and probability basics.

    Learning Practice

  • 6.2

    Game

    This section focuses on the concept of probability and how it applies to games and predictive scenarios.

    Learning Practice

  • 7

    Visuals To Add

    This section discusses the methods of data representation, including graphics and charts used to visually summarize data.

    Learning Practice

  • 8

    Did You Know?

    This section covers intriguing facts about data handling, emphasizing its relevance in today's digital world.

    Learning Practice

  • 9

    Assessment Questions

    This section provides assessment questions aimed at testing understanding of key concepts in data handling.

    Learning Practice

References

maths ch6.pdf

Class Notes

Memorization

Revision Tests

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