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asking-good-questions

Asking good questions

Last reviewed Jun 1, 2026 Content v20260601
Track mode
server_script
Means
Server runner
Reading
~1 min
Level
beginner

This lesson

This lesson teaches Asking good questions: the data science mindset, methods, and communication habits behind evidence-based decisions.

Teams apply Asking good questions in every serious Data Science project—skipping it leaves blind spots in analysis and reviews.

You will apply Asking good questions in contexts like: Analytics teams, product experimentation, research labs, and ML-adjacent engineering in every data-driven company.

Read the narrative, run Python in the playground (stdlib snippets now; install Jupyter, pandas, and scikit-learn locally for full notebooks), and complete MCQs to lock in vocabulary.

When you can explain the previous lesson's ideas in your own words.

Strong questions are specific, actionable, and measurable. Weak: “understand customers.” Strong: “Which signup channel has 30-day retention above 40%?”

SMART-style checklist

  • Specific — who, what window
  • Measurable — numeric success metric
  • Actionable — decision changes if answer is yes/no
  • Feasible — data exists or can be collected

Hypothesis vs question

Hypothesis: “Email channel retains better than paid ads.” Analysis tests with data—not proves personal opinion.

Important interview questions and answers

  1. Q: Actionable?
    A: Stakeholder can change policy based on result.
  2. Q: Vanity metric?
    A: Looks good but does not drive decisions (raw page views only).

Self-check

  1. Rewrite a vague goal as a measurable question.
  2. What makes a metric vanity?

Tip: Ask stakeholders what decision changes if the answer is yes.

Interview prep

Actionable?

Answer should change a decision.

Vanity metric?

Looks good but does not drive action.

Interview tip Lesson completion confidence

Can you explain this lesson in 30 seconds without reading notes?

Not saved yet.

Playground

Runs on the configured server runner (dev: npm run runner with LEARNING_RUNNER_ENABLED=true). Output appears below the editor.

Check yourself

Multiple choice — immediate feedback.

Discussion

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Starter discussion topics

  • Actionable metric?
  • Vanity metric?

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