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Study design

As explained in Starting Data Analytics with Generative AI and Python

The planning of an experiment or analytical investigation, including its procedures, possible outcomes, and interpretation of those outcomes.

Study design turns a business question into a plan before analysis begins. Write a protocol describing the procedures, possible results, and the meaning of each result. This prevents attractive findings from steering the interpretation after the fact. section 3.2

Build the plan around four questions:

  • What business decision or question will the analysis address? section 3.2
  • Which analyses and procedures will be performed? section 3.2
  • What results could occur? section 3.2
  • What action or interpretation follows from each result? section 3.2

A simple decision protocol

For a pricing decision, define the outcomes before inspecting results: if the current price is higher than the purchase price, sell; if equal, hold; otherwise, buy. The protocol may change after preprocessing reveals that some planned analyses are impossible, or when stakeholders revise their priorities. section 3.2

How Starting Data Analytics with Generative AI and Python covers it

How deep it goes
Explains protocol design and revision with a decision example, but does not detail specific analytical methods.
Examples
Uses a price-versus-purchase-price rule to demonstrate predefined outcomes and actions.
What it assumes
Assumes a defined business goal and data context, while teaching the need to plan interpretations before examining results.
What you can do after
Apply it by writing an analysis protocol, mapping possible results to meanings, and revising plans when data or priorities change.
How it connects
Connects descriptive analysis, statistical inference, data preprocessing, stakeholder priorities, and business decisions.

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This explainer was generated by Manning's knowledge graph from the text of Starting Data Analytics with Generative AI and Python. The section links point to the parts of the book it draws on.