Athletes at the 2018 World Figure Skating Championships are evaluated in two rounds of competition: the Short Program, and the Free Skate. The sum of the scores for each skater are then used to determine the medalists. For each of the 24 male skaters at the 2018 World Championship, the scores for each round are displayed in a scatterplot. A graph titled Short Program versus Free Skate has free skate on the x-axis, and short program on the y-axis. A line of best fit goes through (160, 85) and (200, 100). A graph titled Residuals versus Free Skate has free skate on the x-axis, and residual on the y-axis. Points are scattered throughout the graph. Based on the scatterplot and the residual plot, is a linear model appropriate for predicting the Short Program score from the Free Skate score? A linear model is appropriate because the residuals are centered about zero. A linear model is not appropriate because there are outliers in the scatterplot. A linear model is not appropriate because the residual plot does not show a linear pattern. A linear model is appropriate because the scatterplot is roughly linear, and the residual plot does not show a clear pattern.