- #1

ansgar

- 516

- 1

Lets say I have a set of data points with their error and fit a function to that data using 2 parameters just for simplicity.

Now, I know that the covariance ellipse is an ellipse of equal probability contours. But how do we do this in reality? Do I evaluate the chi-squared for different configurations of my 2 parameters (which we assume I have estimated using e.g. chi-squared minimization).. and then what? Should I, for instance if I want to state confidence limit intervals, assume that the center of my ellipse has value = 1 in probablity and then seek those boundaries where chi-squared as reduced to the value exp(-0.5) = 0.683?

Or should I go from my minimum chi-squared value thus obtained from my parameters and then go the boundaries where the chi-squared has reduced by a FACTOR exp(-0.5) = 0.683?