Two variables are defined, a regression equation is given, and one data point is given. \[ \begin{array}{l} \text { Weight = maximum weight capable of bench pressing (pounds) } \\ \text { Training }=\text { number of hours spent lifting weights a week } \\ \text { Weight }=96+11.6 \text { (Training) } \end{array} \] The data point is an individual who trains 5 hours a week and can bench 150 pounds. 3) Find the predicted value for the data point and compute the residual. inter the exact answers. redicted value = \( \square \) lbs tesidual = \( \square \) lbs

To solve the problem, we'll use the given regression equation and the data point provided. **Regression Equation:** \[ \text{Weight} = 96 + 11.6 \times \text{Training} \] **Given Data Point:** - Training = 5 hours per week - Actual Weight = 150 pounds **1. Calculate the Predicted Value:** Substitute the value of Training into the regression equation: \[ \text{Predicted Weight} = 96 + 11.6 \times 5 = 96 + 58 = 154 \text{ pounds} \] **2. Compute the Residual:** Residual is the difference between the actual weight and the predicted weight: \[ \text{Residual} = \text{Actual Weight} - \text{Predicted Weight} = 150 - 154 = -4 \text{ pounds} \] **Final Answers:** - **Predicted value =** \( 154 \) lbs - **Residual =** \( -4 \) lbs