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Pinel DAHOUI
Free guide · PDF (in French)

10 mistakes to avoid when analysing your data

A short, practical guide drawn from my work with companies, institutions and students. Each mistake comes with an example and a tip to avoid it. The guide is currently written in French.

For managers, analysts, researchers and students who work with data, even without being statisticians.

Contents

  1. 01Starting with the data instead of the question
  2. 02Neglecting data cleaning
  3. 03Ignoring missing values, or replacing them with zero
  4. 04Confusing correlation and causation
  5. 05Relying on the average alone
  6. 06Using a sample that doesn’t represent the population
  7. 07Drawing conclusions from very small numbers
  8. 08Running test after test until something is “significant”
  9. 09Showing misleading charts
  10. 10Forgetting to make the analysis reproducible and understandable