Calculations of the scale-invariant power law coefficient of the straight line using the CSSM method; linear regressions were used to evaluate the straight line. A: presents the logarithms of the scales (log(scale)) plotted against the logarithms of the absolute values of the b coefficients (log|bscale) in the regression line for the data plotted in this figure (B, C, D, E and F). The regression line has a slope equal to zero (y = -0.61: standard error = 0, correlation coefficient = 0.2). The linear regression of the logarithm of the inverse of the steps (log(1/h)) is plotted against the logarithm of the roots of the number of the points on the straight line to the absolute value of the determinant of the basic square matrix . Plot B: presents scale 1 (100) unit, where the 0th, 1st, 2nd, 3th and 4th orders consist of 2, 3, 5, 9 and 17 points, respectively. C, D, E and F present the other four scales: 10-1, 10-2, 10-3 and 10-4. The linear regression analyses of the plots are as follows: y = 1.15-0.61x (standard error = 0.061, correlation coefficient = 0.98), y = 1.54-0.61x (standard error = 0.061, correlation coefficient = 0.98), y = 1.93-0.61x, (standard error = 0.07, correlation coefficient = 0.98), y = 2.32-0.61x (standard error = 0.061, correlation coefficient = 0.98) and y = 2.7-0.61x (standard error = 0.06, correlation coefficient = 0.98) for plots A, B, C, D and E; the b coefficients of these regression lines represent (bscale).