General Discussion

In this section we have discussed the general methodology adopted for fitting the data with a function having some physical basis and having some parameters which are to be adjusted to obtain the best fit. While doing this, we have assumed that the errors in the experiment are ``normal'' and the data are not correlated. In that case, we have seen that one can obtain the ``best'' fit by minimizing a quantity called $\chi ^2$. We have stated that this minimization is equivalent to obtaining the largest probability of getting the parameters of the fitting function. We have also seen how one can compute the error in the parameters, which essentially follows from the errors in the experimental measurements themselves. We have also seen how we can determine the goodness of the fit in terms of the $\chi ^2$ distribution function, which is depends on the number of degrees of freedom in the data.