Exercise "Least-squares fit"

1. Make a subroutine that fits a given data-set, {x_i y_i, δy_i}, i=1..n, with a linear combination of given functions, {f_k(x)} k=1..m. The subroutine must return the vector of coefficients and the covariance matrix.
2. Make some interesting fits and check that the reported errors of the fitting coefficients are resonable.

Projects

1. Implement linear least-squares fit for data sets with errors in both x and y: {x_i, δx_i, y_i, δy_i}.