DataForge

Meet the data crew — Catch, Tidy, Graph, Tell, and Guard — who each keep one step of the data pipeline: where data comes from, cleaning it, charting it, reading it, and using it fairly. Then work with real data yourself.

Level 1

For grown-ups — progress report →A private, on-device snapshot mapped to the skill areas practiced. Export a CSV or print — nothing leaves this device.

Work with real data

Two hands-on labs — the same ideas as the DataForge app. Build a pipeline, or predict a result before the data reveals it.

Pipeline Studio Chain blocks — filter, sort, group, chart — over a real dataset and watch the story appear. Hypothesis Lab Predict a statistic first — then the data reveals the real answer. Commit before you see it. Reading Charts Spot what makes a chart misleading — a squashed scale, the wrong chart type, or a cherry-picked slice.

Choose a kit

Each kit is a short round of questions with hints when you need them. Your progress stays on this device.

Kit 1: Data Types & Collection grades 4-5 · 25 questions Kit 2: Graphs & Charts grades 4-5 · 25 questions Kit 3: Mean, Median & Mode grades 5-6 · 25 questions Kit 4: Probability Basics grades 5-6 · 25 questions Kit 5: Data Distributions grades 5-6 · 25 questions Kit 6: Statistical Questions grades 6-7 · 25 questions Kit 7: Data Analysis grades 6-7 · 25 questions Kit 8: Intro to Coding with Data grades 6-7 · 25 questions Kit 9: Data Cleaning & Preparation grades 6-8 · 25 questions Kit 10: Correlation & Causation grades 6-8 · 25 questions Kit 11: Data Visualization Best Practices grades 6-8 · 25 questions Kit 12: Intro to Machine Learning with Data grades 6-8 · 25 questions Kit 13: Cross-Topic Connections grades 5-6 · 25 questions Kit 14: Real-World Applications grades 6-7 · 25 questions Kit 15: Misconceptions & Reasoning grades 6-7 · 25 questions Kit 16: Advanced Synthesis grades 7-8 · 25 questions

Play together · new on the web

Data Duel — a head-to-head kit round for 2–4 players. Take turns on one device, or join a friend in an online room by code. Highest first-try score wins; no chat, no accounts.

⚔️ Start a Data Duel →

Same idea, another world

Something you practice here shows up somewhere else too — that's real learning that travels.

A biased sample skews a statistic the same way skewed data biases an AI model.The shared idea: sampling bias — an unrepresentative sample skews the conclusion (a biased statistic or a biased model)Try AiForge →An unrepresentative sample skews a statistic the same way picking which stories to run slants the news.The shared idea: selection bias — an unrepresentative sample skews a statistic the same way choosing which stories to cover slants the newsTry NewsForge →

More ways to practice

All also on the tab bar above — kept here as quick links:

🔀 Mixed practice — revisit what you’ve learned A short round that shuffles questions from the kits you’ve played, brought back when they’re ready to review. Great for making it stick.

DataForge mascot

Meet the cast — the characters who teach this

Each one stands for an idea you’ll practice. Tap a character to read their illustrated story and hear their audio drama.

Explore all the stories →

📚 Books for DataForge

Read the story, print a workbook, or color the cast — free PDFs to read offline or print at home.

Browse all books →

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