Question: Suppose we want to build a model using a set of explanatory variables to predict risk of cardiovascular disease. Consider the following two models along

  1. Suppose we want to build a model using a set of explanatory variables to predict risk of cardiovascular disease. Consider the following two models along with their adjusted R-squared:
  • Model 1:

Equation: Cardiovascular disease = 8,830 + 81*(smoking)

Adjusted R2: 0.7734

  • Model 2:

Equation: Cardiovascular disease = 8,921 + 77*(smoking) + 7*(BMI) 2 - 9*(age) + 600*(income) + 38*(education)

Adjusted R2: 0.7823

Based on the principle of parsimony, which model you would use and why? [1]

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