Start with a data question
Turn a broad curiosity into a question that data can help answer.
- State a measurable question and identify the observations and variables needed to investigate it.
Data science combines domain knowledge, programming, statistics, and communication to answer questions with data. Begin by making the question specific: what outcome are you trying to understand, for whom, and over what period? Then identify the unit of observation (such as one trip or one customer) and the variables that describe it. A dataset can reveal patterns, but a pattern alone does not prove that one variable caused another.
trip_minutes = [12, 18, 9, 21]
print("trips:", len(trip_minutes))
print("minutes recorded:", sum(trip_minutes))trips: 4 minutes recorded: 60
A clear question guides what you collect and how you analyze it. Check who or what is missing from the data, how each field was measured, and whether the time period represents the situation you care about.
Key takeaways
State a measurable question and identify the observations and variables needed to investigate it.
Check how the data was collected before drawing conclusions.
Explain important assumptions and limitations.
Lesson quiz
3 questions · pass with 3 correct · up to 50 XP
Passing this quiz completes the lesson and keeps your streak going. Questions you miss come back in review sessions later.
Practice: write Python
Write Python in the editor and run it against sample inputs. Python runs locally in your browser using a WebAssembly runtime.
Count observations
Read one JSON array of numeric trip durations and print the number of observations.
- Four trips
- One trip
Python runs in a sandboxed browser worker with a 60 second time limit. Its runtime loads from the Pyodide CDN; your code stays in this browser.
Questions about this lesson
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