**Table 5:** "Inside correlations'' between gradients from new and merged data. The relation Y=pX+a is given (taking errors in account).
X	Y	N	p	a	$\rho$	$\sigma$	$\sigma_0$
$\Delta _{BV}$	$\Delta _{UB}$	39	$1.81\pm .25$	$-.038\pm .005$	.56	.032	.034
$\Delta _{BV}$	$\Delta_{VI}$	43	$1.32\pm .16$	$.031\pm .003$	.63	.023	.025
$\Delta _{BV}$	$\Delta_{BR}$	39	$1.33\pm .05$	$.002\pm .001$	.97	.006	.020
$\Delta _{BV}$	$\Delta _{VJ}$	51	$3.49\pm .44$	$.104\pm .009$	.48	.067	.039
$\Delta _{BV}$	$\Delta _{VK}$	51	$3.95\pm .48$	$.047\pm .010$	.53	.074	.044
$\Delta _{BV}$	$\Delta_{JK}$	51	$1.28\pm .18$	$-.004\pm .004$	.28	.027	.021

(1) X variable; (2) Y variable; (3) number of objects N after rejection of outliers; (4) slope p; (5) zero point a; (6) coefficient of correlation $\rho$ ; (7) dispersion $\sigma$ ; (8) expected dispersion $\sigma_0$ from estimated errors.

Source LaTeX | All tables | In the text

	1 Introduction
	2 Collecting the gradients
	3 Properties of colour gradients
	4 Simulated datasets of colour gradients
	5 Concluding summary
	References