Lesson 1: Looking Carefully

About 30 minutes — Discussion-based lesson

What You Will Learn

This lesson covers:

What observation means in data science
Describing objects with specific attributes (color, size, shape, texture)
The difference between 'looking' and 'observing'
Practice: describe 5 objects without naming them

What observation means in data science

This section covers the key ideas about what observation means in data science. Discuss with your group or family and explore the concepts together.

Describing objects with specific attributes (color, size, shape, texture)

This section covers the key ideas about describing objects with specific attributes (color, size, shape, texture). Discuss with your group or family and explore the concepts together.

The difference between 'looking' and 'observing'

This section covers the key ideas about the difference between 'looking' and 'observing'. Discuss with your group or family and explore the concepts together.

Practice: describe 5 objects without naming them

This section covers the key ideas about practice: describe 5 objects without naming them. Discuss with your group or family and explore the concepts together.

Check Your Understanding

1. What is the difference between looking and observing?

Answer: Looking is quick and casual. Observing means paying careful attention to details — color, size, shape, texture, number. Data scientists observe before they count.

2. What is an attribute?

Answer: An attribute is a specific characteristic of an object — like its color, size, shape, weight, or texture. Describing attributes is how we sort and classify things.

3. Why is observation important for data science?

Answer: Because you cannot collect or organize data about something you have not carefully observed. Observation is always the first step.

4. Name three attributes you could use to describe a pencil.

Answer: Color, length, sharpness, thickness, whether it has an eraser, whether it is wooden or mechanical. Any specific, observable characteristic counts.

Key Takeaways

What observation means in data science
Describing objects with specific attributes (color, size, shape, texture)
The difference between 'looking' and 'observing'
Practice: describe 5 objects without naming them

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