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Learning paths/Applied Data Analysis
Module 02 · Free applied practice

Exploring data and finding useful patterns.

Profile the evidence, inspect distributions, compare groups and explain useful patterns without mistaking them for causes.

6 published lessons310 min suggested studyNo Python or SQL required
Start the first lesson →Download the practice pack ↓
Think before you calculate

Find a pattern.
Check what it means.

Move from a clear analysis plan to a careful exploration of the evidence. Profile the source, inspect response durations, compare groups and challenge the headline with composition and missingness checks.

Before you start: Applied Data Analysis Module 1 or equivalent understanding of grain, cohorts, denominators and descriptive versus causal questions. A calculator or local spreadsheet is sufficient; Python is optional.

Allow about 5 hours and 10 minutes, including exercises. Work with a calculator, text editor or local spreadsheet. Every lesson includes a detailed explanation, practical task, worked solution and knowledge check.

Reuse Module 1’s source unchanged. Learn with a calculator or spreadsheet; optional read-only Python reproduces the outputs. This is a descriptive investigation, not a causal evaluation. Explore practical lessons, worked examples and projects. Follow a published path, practise the method and build work you can explain.

The complete free module

Six lessons. One evidence-led investigation.

Explanation + practice + solution
01

Profile the extract before looking for patterns

Reconcile rows, keys, types and missing fields before interpretation.

45 min02

Understand distributions instead of relying on one average

Calculate response durations with consistent units.

55 min03

Choose charts that reveal rather than manufacture patterns

Match a chart to a distribution, comparison or composition question.

50 min04

Compare groups and separate composition from performance

Calculate group-specific rates and reconcile their denominators.

55 min05

Investigate missingness and alternative explanations

Profile missing ratings by group rather than only overall.

50 min06

Turn explored patterns into an evidence note

Write a concise finding with source fractions and limitations.

55 min
Your evidence starts here

A real practice task.
A manageable dataset.

Start with the profile and worksheet, then build your own summaries and chart plans. The complete pack has thirteen offline files, including a styled worked exploration and optional read-only Python source.

Snapshot: 22 June 2026 00:00 UTC. The cohorts are 1–7 and 8–14 June. Missing ratings remain missing. The same fictional case connects the Applied modules and is separate from Northstar Shop. No real company outcome or customer data is represented.

Open the worked exploration ↗

Complete exploration pack13 offline files: source, exercises, templates and worked evidence.
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Unchanged ticket datasetExact source from Module 01: 24 fictional tickets, UTC timestamps.
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Exploration briefThe new task, scope, populations and interpretation limits.
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Original source dictionaryUnchanged field meanings, missingness and metric policy.
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Source profile checklistRecord counts, validity checks and actions.
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Six practical exercisesDistributions, bins, weights, missingness and the evidence note.
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Chart plan templateDefine questions, axes, boundaries, labels and checks.
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Evidence note templateConnect source, finding, context, limitations and next evidence.
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Complete worked explorationOffline distribution tables, frequency bars and explained solutions.
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Worked lesson solutionsAll six exercises, arithmetic and independent extension.
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Checked outputs and durationsCounts, mean/median, bins, group weights and unavailable states.
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Optional read-only PythonStandard-library worked source; local file only, no website connection.
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Ten-point self-reviewSource, summaries, visuals, group comparisons and interpretation.
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Start here & file guideLocal workflow, exact source reuse and reproduction instructions.
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Ready for review

Can you explain the pattern and its limits?

Review source checks, summaries, visual boundaries, weighted groups and interpretation. Aim for eight points with no zero in summaries or interpretation. This self-review is not an accredited assessment or operational approval.

Begin Module 02 →

Return to Applied Data Analysis ↗

Explore practical lessons, worked examples and projects. Follow a published path, practise the method and build work you can explain. Keep your work locally; no upload is required.