If I understand the point you’re trying to make, you might try an example with curve fitting. If some data in a scatterplot is well explained by a line plus noise, then that’s a better explanation than trying to draw ever more complicated curves that go through all the data exactly. Of course, identifying the very best model that has a few wiggles and less unexplained scatter is actually pretty tricky [c.f. AIC/BIC/cross-validation/splines].
If I understand the point you’re trying to make, you might try an example with curve fitting. If some data in a scatterplot is well explained by a line plus noise, then that’s a better explanation than trying to draw ever more complicated curves that go through all the data exactly. Of course, identifying the very best model that has a few wiggles and less unexplained scatter is actually pretty tricky [c.f. AIC/BIC/cross-validation/splines].