Compare the two models. Would the polynomial model have a logical explanation? A. The linear model has a much higher Upper R squared value than the polynomial model. The linear model will always be better. One might explain it by suggesting that the higher the pre-MBA salary is, the higher the post-MBA salary will be. B. The polynomial model has a much higher Upper R squared value than the linear model. The polynomial will always be better because polynomial models always have high Upper R squared values. One might explain it by suggesting that an MBA will most affect a person's salary if their pre-MBA salary is either very low or very high. C. Both the linear and polynomial models have similar Upper R squared values. Neither model is strictly better than the other because they pass through roughly the same number of data points. One might explain it by suggesting that post-MBA salary is not dependent on pre-MBA salary. D. Both the linear and polynomial models have similar Upper R squared values. The polynomial will always be better because it has additional terms. One might explain it by suggesting that the higher the pre-MBA salary is, the post-MBA salary