Final answer:
Without the specific regression equation, it is not possible to provide the exact predicted weight for a player who is 70 inches tall. The prediction would typically be made by plugging the height into the regression equation of the scatter plot data.
Step-by-step explanation:
The question asks for a prediction of a basketball player's weight based on their height using a line of best fit or least-squares regression line. Although the exact regression equation is not provided in the prompt, typically, one would use the given summary statistics (mean of heights, mean of weights, slope, and y-intercept) to calculate the expected weight. To make a prediction, substitute the height of the player (70 inches) into the regression equation (regression line) and solve for the weight (y).
Generally, the regression equation is in the form: Weight = (slope × Height) + y-intercept. Unfortunately, without the specific slope and y-intercept, we cannot calculate the exact predicted weight. If the student has access to the full scatter plot and summary statistics, I would encourage them to use those specifics to find the exact predicted weight for a player who is 70 inches tall.