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Ordinary Level Mathematics Revision Notes

Topic 1.6: Representing Data

These notes explain Representing Data in simple English so students can understand the topic clearly, not just memorise rules. The Ordinary Level version keeps the focus on the core ideas without unnecessary higher-only pressure.

Curriculum Irish Leaving Certificate
Subject Mathematics
Level Ordinary Level
Premium feature Teacher-style explanations and cleaner study flow
Focus
Understanding before memorising
Interactive
Study tools and guided structure
Question Style
Explained examples and exam practice
Format
Website reading and printable notes

Subtopics Covered

  • The Big Four Data Visualizations
  • Scatter Plots & Correlation
  • 📝 Exam Style Questions

What Makes This Version Better

  • Cleaner Ordinary Level focus with no unnecessary higher-only material
  • Simple teacher-style explanations before each method
  • Worked examples in clear stages
  • Cleaner page flow for student understanding
  • SEO-friendly website naming and branding
Disclaimer This publication is an independent educational resource developed by ExamsLogic and compiled by experienced educators. It is based on publicly available official curricula, including Cambridge, Pearson Edexcel, IB, and the Irish Leaving Certificate. This product is not endorsed by, affiliated with, or sponsored by any examination board or governing authority. All registered trademarks remain the property of their respective owners.
Start Reading Open Study Tools

Learning Objectives

What You Should Be Able To Do

    Interactive Study Tools

    These tools are here to help students slow down and think about the method before rushing to an answer.

    Tool 1

    Study Planner

    Use this to break a topic into small study sessions.

    Plan: A clear breakdown will appear here.
    Tool 2

    Method Reminder

    This quick guide reminds students what to do when they feel stuck.

    • Read the story: what is the question really asking?
    • Choose the method: identify the correct idea before calculating.
    • Show the reason: do not skip the logic.
    • Check the answer: make sure it fits the situation.

    1. The Big Four Data Visualizations

    Simple explanation: This section explains how to read, organise, and interpret data in a clear exam-friendly way.

    Choosing the right graph is key. Here is what you need to know for the exam:

    • Bar Charts: Used for Categorical or Discrete data. Bars must have gaps between them!
    • Histograms: Used for Continuous data. There are no gaps between bars because the data is continuous. The area of the bar often represents frequency.
    • Stem-and-Leaf Plots: Excellent for keeping the original data values visible while showing distribution. Always include a key!
    • Scatter Plots: Used for two numerical variables to show correlation.
    Examiner Tip
    💡 Examiner Tip: For Histograms, if the class intervals are unequal, you must use Frequency Density on the Y-axis. Frequency Density = Frequency / Class Width. This is a common Higher Level trap!

    2. Scatter Plots & Correlation

    Simple explanation: This section explains the main idea in simple English first, then builds toward the formal method used in exam questions.

    Scatter plots show the relationship between two variables (x, y).

    • Strong Positive Correlation: Points form a tight line going UP.
    • Strong Negative Correlation: Points form a tight line going DOWN.
    • No Correlation: Points are scattered randomly like a cloud.
    Common Mistake
    ❌ Common Mistake: Confusing "Correlation" with "Causation". Just because ice cream sales and sunburns are positively correlated does not mean ice cream *causes* sunburns! Both are caused by hot weather (a hidden variable).

    📝 Exam Style Questions

    Simple explanation: This section explains the main idea in simple English first, then builds toward the formal method used in exam questions.

    Easy Q1: Why are there gaps between the bars of a Bar Chart but not a Histogram?

    Medium Q2: Describe the correlation in a scatter plot where the points are tightly clustered moving from the top-left to the bottom-right.

    A1: Bar charts represent discrete/categorical data where the categories are separate. Histograms represent continuous data which flows without gaps.

    A2: This is a strong negative correlation.