One method used to measure the speed of supercomputers is the number of floating-point mathematical operations the computer can perform in one second. This is often referred to by the acronym FLOPS. For many years since 1992, the number of FLOPS performed by the largest supercomputer available that year was recorded. A graph titled F L O P S versus Years since 1992 has years since 1992 on the x-axis, and F L O P S (Billions) on the y-axis. Points curve up exponentially. A graph titled l n (F L O P S) versus Years since 1992 has years since 1992 on the x-axis, and l n (F L O P S) on the y-axis. Points increase in a line with positive slope. A graph titled l n (F L O P S) versus l n (Years) has l n (years) on the x-axis, and l n (F L O P S) on the y-axis. Points curve up exponentially. Based on the three graphs shown, which type of model is most appropriate for comparing years to FLOPS? A linear model, because the scatterplot of years and ln operations is roughly linear. A power model, because the scatterplot of years and operations shows a steep curve. An exponential model could be appropriate because the scatterplot of years and ln(operations) is roughly linear. The next step is to look at the residual plot. A power model, because the scatterplot of ln(years) and ln(operations) shows the strongest linear relationship.