The overall strategy in fitting a curve function yfx to a se

The overall strategy in fitting a curve (function y=f(x)) to a set of data points is to minimize the discrepancy between the data points y1 and the curve f(xi). A common method is to minimize the sum of the squares of the errors, \'\'SSE\'\'. Suppose we have a collection of N experimentally determined values {(xi,yi)}, and a proposed function f(x). Write an expression for SSE for this situation.