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Data Interview Question

Interpreting Logistic Regression Coefficients

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Requirements Clarification & Assessment

  • Objective: Understand the interpretation of logistic regression coefficients in the context of predicting student exam success based on study hours.

  • Data Provided:

    • Logistic regression model output with coefficients for intercept and study hours.
    • Statistical metrics: Coefficient, Standard Error, z-value, and P-value.
  • Key Variables:

    • Dependent Variable: Probability of passing the exam (binary outcome: pass/fail).
    • Independent Variable: Number of study hours (ranging from 0 to 6).
  • Model Equation:

    • log(P/(1-P)) = β₀ + β₁ * Hours
    • Where β₀ = -4.0777 (intercept) and β₁ = 1.5046 (study hours coefficient).
  • Clarifications Needed:

    • Assumptions made during model training (e.g., data distribution, handling of outliers).
    • Context of the study (e.g., student population characteristics, exam difficulty).
    • Any additional variables or potential confounders considered.