The equation \( \hat{y}=1.2676 x+79.6645 \) models Fred's systolic blood pressure, in mm/HG, over his life span, where \( x \) is Fred's age. According to the regression equation, what is the approximate systolic blood pressure of Fred at the age of 55 ? about \( 135 \mathrm{~mm} / \mathrm{HG} \) about \( 149 \mathrm{~mm} / \mathrm{HG} \) about \( 159 \mathrm{~mm} / \mathrm{HG} \) about \( 165 \mathrm{~mm} / \mathrm{HG} \)

To find Fred's systolic blood pressure at the age of 55, we can substitute \( x = 55 \) into the equation \( \hat{y} = 1.2676 \cdot x + 79.6645 \). Calculating: \[ \hat{y} = 1.2676 \cdot 55 + 79.6645 \approx 69.708 + 79.6645 \approx 149.3725 \text{ mm/HG} \] So, the approximate systolic blood pressure of Fred at the age of 55 is about \( 149 \mathrm{~mm} / \mathrm{HG} \). Over the years, various factors influence blood pressure, including lifestyle choices, diet, and stress levels. Understanding how these factors interact with age can empower individuals to maintain a healthier lifestyle. So, while the regression model gives a prediction, it's essential to consider personal health habits! When interpreting regression equations, it's easy to overlook the importance of context. Always remember that these models provide estimates based on historical data and may not account for sudden lifestyle changes or health conditions. Making lifestyle adjustments proactively can lead to better outcomes than simply relying on predicted trends!