On Nov 28, 9:37 am, djh <halitsk...@att.net> wrote: > Results (!!) on average slopes and means for a1_N_1_C (complement > instead of core subset) > > Len > Int Avg Slope Mean u' > > 1 -2.225882168 0.482402362 > 2 -2.315512399 0.469544417 > 3 -0.769858117 0.485742217 > 4 -1.697049757 0.451420560 > 5 -2.069842267 0.459536902 > 6 -4.427566827 0.457327711 > 7 -0.941379623 0.458781950 > 8 -2.069096413 0.445826306 > 9 -1.620229799 0.442040277 > 10 -3.764328472 0.449422937 > 11 -7.882327621 0.458400090 > 12 -11.82556530 0.458971482 > > I don?t know if the above results, when compared to the results in the > previous post for a1_N_1_S, do or don?t indicate that your definition > of average slope is OK. > > As in the a1_N_1_S case, Mean(u?) inversely correlates with LenInt. > > But unlike the a1_N_1_S case, average slope ALSO inversely correlates > with LenInt. > > I can readily make a scientific interpretation of these two sets of > results, but don?t want to do so if you think that these two sets of > results indicate a problem with the definition of average slope.
The plots look nice, but each point needs standard error bars. The average slope is a1 + 2*a2*mean_x, so its standard error is sqrt[ var(a1) + 4*var(a2)*(mean_x)^2 + 4*cov(a1,a2)*mean_x ], with df = n-3.