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Independent vs Dependent Variables

Run the Independent vs Dependent Variables MicroSim Fullscreen

About This MicroSim

This interactive scatter plot visualization helps students understand the fundamental concept of independent and dependent variables by exploring the relationship between study time and test scores.

Key Concepts

  • Independent Variable (X-axis): Hours Studied - This is what you control or change
  • Dependent Variable (Y-axis): Test Score - This is what you measure or observe

Interactive Features

Control Description
Add Student button Adds a random student data point based on current relationship strength
Generate Class of 30 button Creates a realistic dataset of 30 students
Clear All button Removes all data points
Relationship Strength slider Controls how predictable scores are from study time (0-100%)
Show Trend Line toggle Display/hide the regression line
Show Prediction toggle Show predicted score when hovering over the plot
Click on plot Add a student at that exact study time/score location

Statistics Panel

The right panel displays:

  • Number of students in the dataset
  • Average study time (hours)
  • Average test score (points)
  • Correlation strength with emoji indicator (💪 strong, 👍 moderate, 🤷 weak)

Visual Elements

  • 🎓 Regular student data points
  • 🌟 Outlier students (those who significantly beat or missed expectations)
  • Blue trend line showing the best-fit relationship
  • Light blue confidence band around the trend line
  • Orange dashed prediction lines when hovering

Iframe Embedding

You can include this MicroSim on your website using the following iframe:

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<iframe src="https://dmccreary.github.io/data-science-course/sims/independent-dependent-variables/main.html"
        height="502px"
        width="100%"
        scrolling="no">
</iframe>

Lesson Plan

Learning Objectives

By the end of this activity, students will be able to:

  1. Identify which variable is independent and which is dependent in a scenario
  2. Explain that the independent variable is what you control, and the dependent variable is what you measure
  3. Observe how correlation strength affects the scatter of data points
  4. Predict approximate outcomes based on the trend line
  5. Recognize that relationships show tendencies, not guarantees (there's always variation)

Guided Exploration (15-20 minutes)

Part 1: Understanding the Relationship (5 min)

  1. Start with the default settings (70% relationship strength, 10 students)
  2. Ask students: "Which variable does the researcher control?"
  3. Ask: "What happens to test scores as study time increases?"
  4. Click "Generate Class of 30" to see a more complete picture

Part 2: Exploring Correlation Strength (5 min)

  1. Set relationship strength to 100% - observe tight clustering around the line
  2. Set relationship strength to 50% - observe more scatter
  3. Set relationship strength to 10% - observe near-random scatter
  4. Discuss: "What does a 'strong relationship' mean in real life?"

Part 3: Making Predictions (5 min)

  1. Enable "Show Prediction" and hover over the plot
  2. Ask: "If someone studies 6 hours, what score might they expect?"
  3. Click on the plot to add students at specific locations
  4. Discuss outliers: "Why might someone study a lot but still score low?"

Discussion Questions

  1. What are some other examples of independent and dependent variables?
  2. Water amount (independent) → Plant growth (dependent)
  3. Exercise time (independent) → Fitness level (dependent)

  4. Temperature (independent) → Ice cream sales (dependent)

  5. Why do we call one variable "dependent"?

  6. Can we ever be 100% certain about a prediction? Why or why not?

  7. What does the correlation emoji (💪, 👍, 🤷) tell us about the data?

Extension Activities

  • Have students design their own experiment with independent/dependent variables
  • Discuss the difference between correlation and causation
  • Explore what happens when you add extreme outliers manually

Technical Details

  • Library: p5.js 1.11.10
  • Canvas Size: 700×500px (responsive width)
  • Draw Height: 400px
  • Control Height: 100px
  • Bloom's Taxonomy Level: Apply (L3)
  • Recommended Duration: 15-20 minutes

Image Note

Remember to create a screenshot of this MicroSim and save it as independent-dependent-variables.png in this directory for social media preview images.