Confirmatory vs Exploratory Data Analysis

Confirmatory vs Exploratory Data Analysis

  • Confirmatory Analysis

    • Inferential Statistics – Deductive Approach
      • Heavy reliance on probability models
      • Must accept untestable assumptions
      • Look for definite answers to specific questions
      • Emphasis on numerical calculations
      • Hypotheses determined at outset
      • Hypothesis tests and formal confidence interval estimation
    • Advantages
      • Provide precise information in the right circumstances
      • Well-established theory and methods
    • Disadvantages
      • Misleading impression of precision in less than ideal circumstances
      • Analysis driven by preconceived ideas
      • Difficult to notice unexpected results
  • Exploratory Analysis

    • Descriptive Statistics – Inductive Approach
      • Look for flexible ways to examine data without preconceptions
      • Attempt to evaluate validity of assumptions
      • Heavy reliance on graphical displays
      • Let data suggest questions
      • Focus on indications and approximate error magnitudes
    • Advantages
      • Flexible ways to generate hypotheses
      • More realistic statements of accuracy
      • Does not require more than data can support
      • Promotes deeper understanding of processes
        • Statistical learning
    • Disadvantages
      • Usually does not provide definitive answers
      • Difficult to avoid optimistic bias produced by overfitting
      • Requires judgement and artistry – can’t be cookbooked