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Scientific method

As explained in Grokking Statistics

The scientific method is a systematic approach that formulates an objective or question before collecting and analyzing evidence.

The scientific method starts with a specific objective or question, then collects and analyzes evidence suited to it. This focused sequence makes data collection more manageable and reduces spurious findings compared with searching through data first. section 2.2

Assessing golf skill with photographs

Instead of asking whether someone is broadly good at golf, collect targeted evidence: photographs of the person mid-swing, celebrating at the 18th hole, or holding a scorecard. Then question the evidence: the celebration might be for someone else, and the scorecard might be forged. Missing context, bias, and inaccurate data can still produce wrong conclusions. section 2.2

Use the method as a practical data check:

  • Define the objective before collecting evidence. section 2.2
  • Ask how the data was created, what influenced it, and what it fails to capture. section 2.2
  • Check whether the evidence represents the domain before trusting conclusions or models. section 2.2

How Grokking Statistics covers it

How deep it goes
Explains focused objectives and evidence checks through one example, but does not detail formal experimental procedures.
Examples
Uses family photographs, golf swings, celebrations, and scorecards to expose focused measurement and misleading context.
What you can do after
Evaluate data-driven claims by narrowing objectives and checking evidence for context, bias, accuracy, and representativeness.
How it connects
Connects scientific method with data mining, statistical analysis, machine learning, bias, context, and representative data.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Grokking Statistics. The section links point to the parts of the book it draws on.