Distance Scale on Logistic Regression Coefficients

Requirements Clarification & Assessment

1. Understanding the Problem:

   • We are tasked with developing a logistic regression model to predict the likelihood of a rider accepting a ride based on the distance between the rider's current location and the pickup point.

2. Identifying the Key Components:

   • Outcome Variable: Rider's decision to accept the ride (binary: 1 for acceptance, 0 for rejection).
   • Predictor Variable: Distance between the rider's current location and the pickup point.

3. Clarifying the Impact of Distance:

   • Determine how changes in the distance measurement scale (e.g., miles to kilometers) affect the model's coefficients and interpretability.

4. Assumptions:

   • The relationship between distance and ride acceptance is linear in the log-odds space.
   • Distance is the sole predictor, simplifying the assessment of scale changes.

5. Objective:

   • Interpret the logistic regression coefficient for distance and understand the implications of altering the distance measurement scale.