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Data Analysis and Visualization with Python / Module 1

Module 1 check

Module 1 Assessment: Analysis Framing Check

Assessment ID: DAV-M01-QA01 Estimated active time: 20-30 minutes

Part A: Short answers

Answer in one or two sentences.

  1. Why should a data analysis project start with a question?
  2. What is the unit of analysis?
  3. Why should raw data not be overwritten?
  4. What is the difference between a measure and a dimension?
  5. Why should a limitation be written before analysis starts?

Part B: Repair the question

Weak question:

> What is happening with learners?

Rewrite it as a clearer data question. Your question must name:

  • a measure;
  • a group, time period, or comparison;
  • the reason the answer could be useful.

Part C: Notebook outline

Create headings for a notebook that answers your repaired question.

Minimum headings:

  • Question
  • Setup
  • Load data
  • Inspect data
  • Clean data
  • Analyze
  • Visualize
  • Conclusion
  • Limits

Rubric

LevelEvidence
PassThe learner writes a clear question, identifies row meaning, creates a notebook outline, and names a realistic limitation.
ReviseThe question is useful but still vague, or the row meaning is unclear.
Not yetThe answer mainly says to "analyze the data" without naming a question, unit, or limit.