Session 8 of 8 · Grade 3 Data Science · CAPSTONE

🏆

Your Data Project

Run the complete data cycle — start to finish — on your own

~60 minutes Grade 3 · Ages 8–9 Full Data Cycle

Today's Plan

The Final Session

0–5 min🔁 Warm-Up — quick tour of everything we've learned
5–10 min📖 Project intro — your mission for today
10–25 min✍️ Phase 1: Plan — choose your question and collection method
25–40 min📋 Phase 2: Collect — survey classmates, record with tally marks
40–50 min🗂️ Phase 3: Organize + Visualize — frequency table and chart
50–57 min🎤 Phase 4: Present — share your chart and what it says
57–60 min🎉 Celebration — you are now a data scientist!

Warm-Up · 5 min

Everything You've Learned

👁️

Sessions 1–2

Notice & Ask Good Questions

📋

Sessions 3–4

Collect & Organize Data

📊

Sessions 5–6

Visualize & Interpret

🕵️

Session 7

Evaluate & Question

Today in Session 8: you run ALL of these steps — on your own question!

Your Mission

What You'll Do Today

This is exactly what real data scientists do. Every. Single. Time.

Phase 1 · 15 min

✍️ Phase 1: Plan Your Project

Write your question

It must be fair and data-answerable

It needs 3–5 specific answer choices

Ask: "Could I count the answers?"

Good examples:

"What is your favorite season?"
"How do you get to school?"
"What is your favorite subject?"

Plan your collection

Who will you ask? (your sample)

How many people? (aim for 10+)

Method: survey, observation, or measurement?

How will you record? (tally marks!)

✅ Check: Is your question fair? Is it specific? Is it answerable with data?

Phase 2 · 15 min

📋 Phase 2: Collect Your Data

Remember the survey rules from Session 3:

Ask exactly as written

Give the choices — don't suggest one

Record immediately

Each person once only

Say "thank you!"

Phase 3a · part of 10 min

🗂️ Phase 3: Organize — Frequency Table

      Transfer your tally marks into a clean frequency table. Remember: 3 columns — Category · Tally · Frequency — and a Total row at the bottom.
    

Quick self-check before moving to the chart:

☐ All categories are listed in the left column
☐ Tally marks are copied from my recording sheet
☐ Frequency numbers are correct
☐ Total row is filled in
☐ Total matches how many people I asked

Phase 3b · part of 10 min

📊 Phase 3: Visualize — Draw Your Chart

Bar chart checklist

☐ Title at the top
☐ Category labels on one axis
☐ Even number scale starting at 0
☐ Each bar = correct height
☐ Color used

Pictograph checklist

☐ Title at the top
☐ Category labels on the left
☐ Key explains what 1 symbol = how many
☐ Correct number of symbols per row
☐ All symbols same size

Phase 4 · 7 min

🎤 Phase 4: Present Your Findings

You have 60–90 seconds. Use this structure to guide what you say:

1."My question was: _______________"

2."I asked ___ people using _______________" (method)

3.[Show chart] "My chart shows that _______________" (observation)

4."This might mean that _______________" (inference)

5."If I could do this again, I would _______________" (reflection)

You've got this. You've done every one of these steps already — this is just putting it all together!

Standards

What Makes a Strong Data Project?

Good Question

Fair — no leading language

Specific answer choices

Answerable with data

Interesting — you actually want to know!

Good Data

Collected from 10+ people

Recorded consistently

Frequency total checks out

Tally marks used correctly

Good Communication

Chart has title, labels, scale/key

At least 1 specific observation

At least 1 thoughtful inference

Conclusion answers original question

Reflection

You Just Ran the Full Data Cycle

👁️
Notice

→

❓
Ask

→

📋
Collect

→

🗂️
Organize

→

📊
Visualize

→

🔍
Interpret

→

🕵️
Evaluate

→

🎤
Communicate

      Every data scientist in the world follows this same cycle. You are one of them now.
    

Connecting to the World

Data Science Is Everywhere

🏥 Health

Doctors collect data on patients to find what treatments work

Scientists track disease to keep communities safe

🌍 Environment

Scientists measure temperature data over decades to track climate change

Wildlife trackers count animals to protect endangered species

🎮 Technology

Apps collect data on what features you use to make them better

Video games use data to balance difficulty

      The skills you learned this course — asking good questions, collecting fairly, visualizing honestly, reading critically — are real data science skills.
    

Reflection

One Last Reflection

"The most important thing I learned about data is ___."

Possible answers — all valid!

"You have to ask fair questions"

"Charts can trick you"

"Data helps you make better decisions"

"You need enough people in your sample"

"Organizing messy data takes real skill"

Also think about:

What was the hardest part of the whole course?

What surprised you most?

What would you teach someone else first?

What question would you investigate next?

Celebration

⭐ ⭐ ⭐

Certificate of Achievement

This certifies that

________________________________

has successfully completed

Data Science for Young Minds · Grade 3

and has demonstrated the skills of

Observation · Questioning · Collection · Organization
Visualization · Interpretation · Critical Thinking

⭐ ⭐ ⭐

Course Complete 🎉

🏆

You Are a Data Scientist!

      Thank you for being curious, asking good questions, and working hard through all 8 sessions.
    

What you can do now

Ask data-answerable questions

Collect data fairly and carefully

Build frequency tables and charts

Read and question any chart you see

Tell a story with data

Keep exploring!