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Variable Types Concept Map

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Description

This interactive concept map helps students understand the fundamental classification of variables in statistics. The hierarchical structure clearly shows how variables branch into two main categories:

  • Categorical Variables: Variables that name categories or groups, where values are labels rather than numbers (like eye color, zip code, or blood type)
  • Quantitative Variables: Variables with numerical values that represent quantities or amounts

Quantitative variables are further subdivided into:

  • Discrete Variables: Can only take specific, countable values (often integers), like the number of children or cars owned
  • Continuous Variables: Can take any value within a range, including decimals, like height, weight, or temperature

Interactive Features

  • Hover over any node to see its definition and 3-4 examples
  • Click on a node to highlight its branch (ancestors and descendants) while dimming other nodes
  • Click again on the same node to clear the selection and show all branches

The color-coded branches help reinforce the classification structure:

  • Purple/indigo for the root "Variable" node
  • Green for the Categorical branch
  • Orange/yellow shades for the Quantitative branch and its children

Lesson Plan

Learning Objective

Students will be able to classify variables into categorical and quantitative types, and further subdivide quantitative variables into discrete and continuous.

Grade Level

High School (AP Statistics) or Undergraduate Introduction to Statistics

Prerequisites

  • Understanding of what data and variables are
  • Basic familiarity with numbers vs. categories

Duration

15-20 minutes

Activities

  1. Exploration (5 minutes): Have students hover over each node to read definitions and examples. Ask them to notice the hierarchical structure.

  2. Classification Practice (10 minutes): Present the following variables and have students classify each:

  3. Number of siblings (Quantitative - Discrete)
  4. Favorite sport (Categorical)
  5. Time to run a mile (Quantitative - Continuous)
  6. Letter grade (Categorical)
  7. Temperature in Fahrenheit (Quantitative - Continuous)

  8. Number of text messages sent today (Quantitative - Discrete)

  9. Discussion (5 minutes): Ask students why it matters whether a variable is categorical vs. quantitative, or discrete vs. continuous. Connect to how we might display and analyze each type differently.

Assessment Questions

  1. What is the key difference between categorical and quantitative variables?
  2. Give an example of a discrete variable that is NOT a count.
  3. Can a variable that uses numbers (like zip codes) be categorical? Explain.
  4. Why might the same characteristic be measured as discrete or continuous depending on how we collect the data?

Extension

Have students create their own examples for each category from a dataset they encounter in their daily lives (sports statistics, social media metrics, health data, etc.).

References