Answer:
SAT vs. IQ because the data points are closer to the trend line.
Step-by-step explanation: The accuracy of linear model is based on the sum of the squared error between the actual and predicted data. Therefore in drawing our trend line, we want one in which gives the least sum of squared error(distance between trend line and the actual data point). With such a trend line, we'll get a more accurate prediction from our model. The rate of change does not rely dictate accuracy of a model, it only explains how a variable changes in relation to another. From both graphs, the data point on the SAT v IQ graph AR closer to the trend lines and as such will produce a lower sum of squared error than the GPA v IQ model.