for the Gaussian and non-Gaussian case respectively. Inspecting table 4 already reveals some discrepancies between the Gaussian and the actual error. In particular the correct error intervals are always smaller to the left of the peak of the posterior and larger to the right, showing a skewness in its distribution. This trend can be seen very well in figure , where the confidence level q = 68.3, 95.4, 99.7% contours (compare with equation ( ), corresponding to 1-σ, 2-σ and 3-σ for a Gaussian respectively) are plotted for the exact (blue) and the Gaussian posterior (red). It should be noted that case A is again only for consistency, since in already investigated the full shape of the posterior but was not able to include errors in the independent variable in the analysis. Another visible trend is that the differences between the Gaussian and exact contours becomes larger for larger values of q. The reason for this is that the exact distribution has a much more pronounced tail to large values of r i than the Gaussian one. In case B one can see the largest differences and the corresponding error estimates differ by a factor of more than 2, even more so the Gaussian 99.7% contour lies within the 95.4% contour of the exact distribution.