The multiple regression and the simple regression give you different numbers for the effect of fertilizer on yield. Here are some ideas that you can use in your comment:
To explain the difference in prediction between the two methods, you can use these ideas, in addition to (or instead of) the ideas in Assignment 3:
Here's another way to think about it:
Imagine that, instead of rain from heaven, the different amounts of water on the different fields came from a practical joker who deliberately put more water on the fields on which you put more fertilizer. He wants to fool you into thinking that the fertilizer's effect is bigger than it really is. (Maybe he sells fertilizer for a living!) If you use the simple regression to predict, you will fall for his scheme. If you then apply 800 pounds of fertilizer -- an amount that is way above the average of the other fields -- to a new field, and if the joker doesn't add a corresponding above-average amount of water, the yield will disappoint you. You won't get as much as the simple regression predicted.
By the way, if your rain coefficient is not statistically significant, the difference between the two predictions will not be statistically significant either. If you compare the confidence intervals of the predictions, you'll see that each prediction is inside the other prediction's 95% confidence interval.