Modeling correlation and regression

2024-07-26

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Lecture 3 Outline

  • Testing and summarizing relationship between 2 variables (correlation)
    • Pearson \(r\) analysis (param)
      • (numerical variables)
    • Spearman’s test (no param)
  • Measures of association
    • Chi-Square Test of Independence
      • (categorical variables)
    • Fisher’s Exact Test
  • From correlation/association to prediction/causation
    • The purpose of observational and experimental studies
  • Widely used analytical tools
    • Simple linear regression models
    • Multiple Linear Regression models
  • Shifting the emphasis on empirical prediction
    • Introduction to Machine Learning (ML)
    • Distinction between Supervised & Unsupervised algorithms