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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
- 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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