Data and Chance · Spring Term

Measures of Central Tendency: Mean, Median, Mode

Calculating and interpreting the mean, median, and mode for a given set of data.

Key Questions

  1. Explain what the mean, median, and mode represent in a data set.
  2. Calculate the mean, median, and mode for various data sets.
  3. Analyze which measure of central tendency is most appropriate for different types of data and contexts.

NCCA Curriculum Specifications

NCCA: Junior Cycle - Statistics and Probability - S.1.3
Class/Year: 2nd Class
Subject: Mathematical Explorers: Building Foundations
Unit: Data and Chance
Period: Spring Term

Suggested Methodologies

Project-Based Learning

Extended projects with real-world deliverables

45–60 min

Learn more about Project-Based Learning

Peer Teaching

Students prepare and deliver mini-lessons to classmates

30–55 min

Learn more about Peer Teaching

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Planning templates for Mathematical Explorers: Building Foundations

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5E Model

The 5E Model structures lessons through five phases (Engage, Explore, Explain, Elaborate, and Evaluate), guiding students from curiosity to deep understanding through inquiry-based learning.

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Math Unit

Plan a multi-week math unit with conceptual coherence: from building number sense and procedural fluency to applying skills in context and developing mathematical reasoning across a connected sequence of lessons.

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Math Rubric

Build a math rubric that assesses problem-solving, mathematical reasoning, and communication alongside procedural accuracy, giving students feedback on how they think, not just whether they got the right answer.

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Creating and interpreting bar charts and pie charts to represent and analyze categorical data.

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Calculating theoretical probability and conducting simple experiments to determine experimental probability.

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Range and Spread of Data

Calculating and interpreting the range as a measure of the spread or dispersion of data.

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Misleading Statistics and Graphs

Identifying and analyzing how statistics and graphs can be manipulated to present a biased or misleading view of data.

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