Lesson 10: Your Data Project
This is your capstone lesson. You'll design, build, and present a complete data analysis project: choose a topic, define your question, collect or simulate data, compute statistics, create a chart, and write up your findings.
Key Concepts
Choose a Topic
Pick something you're curious about. Oklahoma weather temperatures by month. School lunch ratings. Free-throw percentages. A good topic has a clear question and numeric data you can actually get.
Define Your Question
Good question: "Do students in Tulsa score higher than students in OKC on average?" Bad question: "What are scores like?" Your question should be specific enough to answer with one or two statistics.
Collect or Simulate Data
Real: surveys, websites, public datasets (data.gov, weather.gov, census.gov). Simulated: use Python's random module to generate realistic fake data for practice.
Analyze & Visualize
Compute mean, median, and range. Pick the right chart for your question (comparing groups → bar chart, trend over time → line chart, relationship → scatter plot). Make your chart readable — add a title and labels.
Write Your Finding
One paragraph: What did you find? Is it what you expected? What might explain it? What would you investigate next? This is the part employers and teachers actually care about.
🔬 Interactive Lab: Project Planner
Fill in your project plan. The tool generates a Python code outline and a chart to get you started.
✅ Check Your Understanding
1. What makes a good data question?
2. Where can you find real free public datasets?
3. Why is the written conclusion the most important part of a data project?