I just finished my dissertation results and trying to interpret them and very confused. Basically, X and Y are not correlated but then when I put X in my regression model with a few other variables X significantly predicts Y. I've been explained this statistically and somewhat understand it --- that when you control for other things the relationship changes, but theoretically it makes absolutely no sense. Can someone give me an example using variables showing how they are not related when looking at them in a vacuum but then becomes a significant predictor in another instance? Having a hard time writing discussion because of this. Thanks.