I have a lot of measurements of some quantity y as a function of x. All these data points are such that no y_i is taken at the same x_i. So I want to fit some kind of function to all these data point, but I want an uncertainty in the y_i's. Normally if I had say 10 y_i measured at the same x_i I would calculate the standard deviation and use that as the uncertainty. But since all my y_i are taken at different x_i, I can't do that. How do I give a meaningful uncertainty to all the y_i. It seems weird that if I have 10 measurements of 10 different y_i (100 data points in total) that I should get something much less uncertain than if I have 100 measurements of 100 all different y_i.