The narrow distribution of each P i (•) in Figure enables us to conclude that the contribution to parameter variability from noise associated with each particular experiment is minimal for all five parameters estimated. From perusal of Figures and, we can conclude that while the degree of experiment-to-experiment variation changes with respect to each parameter, it is in general significantly greater than the parameter variability from noise alone (i.e. the width of each P i (•)). From the hyper-parameter samples we can calculate the distribution P (•) of each parameter that would be expected from another repeat experiment (shown in Figure , left column). Quantitatively, the parameter mean values (with one standard deviation values in parenthesis) as deduced from this analysis are as follows: