Everything else is ready: study the parts, the key terms and the quiz below.
- Part 11Set the decision and seal the project holdout
- Part 22Check the source and derive the outcome balance
- Part 33Audit categorical feature codes before interpreting them
- Part 44Inspect numerical fields together, without choosing a model
- Part 55Count subgroups before interpreting their rates
- Part 66Assemble a one-page report that changes the next step
- Part 77Reproduce the report and hand off the project challenge
Project Lab: End-to-End EDA for an ML Decision
Produce a reproducible data report that changes a modelling decision, not a gallery of attractive plots.
In this lesson7 parts
- 01Set the decision and seal the project holdout
- 02Check the source and derive the outcome balance
- 03Audit categorical feature codes before interpreting them
- 04Inspect numerical fields together, without choosing a model
- 05Count subgroups before interpreting their rates
- 06Assemble a one-page report that changes the next step
- 07Reproduce the report and hand off the project challenge
Key terms
The words this lesson introduces, each in one line. The module’s glossary collects them all.
- target
- The recorded outcome a future model is intended to predict: next-month default, coded 0 or 1.
- holdout
- Rows reserved from model-directed exploration for later evaluation: the 6,000 pinned IDs.
- data-quality check
- A test of recorded fields against the intended analysis.
- base rate
- Observed frequency of the target outcome in a stated set of rows: 5,317 / 24,000 = 22.15%.
- feature code
- A stored numeric value standing for a documented category or status.
- EDA report
- Reproducible observations linked to explicit limits and next checks.
Quiz 5 questions
Your first pick on each question is the one that counts, and a right one earns a coin. Getting one wrong here is how the lesson sticks.
Practice
Problems to solve in your own notebook. Each states the problem, not the steps: working out the steps is the exercise. Level A applies the lesson, B combines it with earlier ones, C stretches it.
The self-checking notebook for this lesson is Stats Module 2 project · A training-only credit EDA report.
Common mistakes
What you will see when it goes wrong, why it happens, and the fix.
Where it’s used
Where this lesson’s ideas turn up in real work.