Predictors of Average Life Expectancy Term Paper

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In this particular sample, looking at the adjusted R2 is somewhat pointless, as the data is based on a population, not a sample, and as such, the adjusted R2 does not add a significant contribution to our interpretation of the data.

Discussion of the empirical results from the regression analysis

The results of the regression analysis support the predictions that each of the identified independent variables is an important and significant predictor of average life expectancy at the county level.

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Higher percentages of obese individuals, smokers, low rates of exercise and small numbers of active primary care physicians predicted lower average life expectances at the county level. These results echo past research that has linked these variables to specific health outcomes and highlight the importance of focusing on these issues as important areas for intervention with respect to improving health, reducing health care costs, and general health promotion.

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