# Explanation To predict the average score of a basketball player who is 70 inches tall using the given linear regression equation, we need lớn plug the value of the player's height into the equation and solve for the predicted average score. ### Step 1 Identify the linear regression equation. The equation is partially given and needs lớn be completed with the missing coefficient and constant term. ### Step 2 Complete the regression equation using the given parts of the equation. The equation is given as \( hắn \approx 0.703x - \square \), and the constant term is given as \( \square \chi \Rightarrow 22.991 \). So, the complete equation should be \( hắn \approx 0.703x - 22.991 \). ### Step 3 Substitute the value of \( x \) (the player's height in inches) into the regression equation lớn predict the value of \( hắn \) (the player's average points per game). For a player who is 70 inches tall, we will phối \( x = 70 \). ### Step 4 Calculate the predicted value of \( hắn \) by evaluating the regression equation with \( x = 70 \). ### Step 5 Interpret the result lớn provide the prediction for the average score per game for a basketball player who is 70 inches tall.