Because of nonnormal distribution data for each mRNA, Spearman's correlation coefficients were calculated to detect the

linear correlation between esophageal IRP and the corresponding mRNA in achalasia patients.

The Pearson's

linear correlation coefficients between the PH, SD, NN, and NL traits with fresh and dry matter of pods (FMP and DMP) showed low magnitude (r [less than or equal to] [absolute value of (0.249)]) and the direct effects were reduced (direct effect [less than or equal to] [absolute value of (- 0.2578)]), which indicates absence of linear relation of cause and effect between traits.

The

linear correlation coefficient was weak ([R.sup.2] = 0.246) (Fig.

The

linear correlation analysis revealed that the start date of 'End of flowering' correlated significantly only with average T of October at both study areas (Table 2).

No

linear correlation was detected between age and corneal curvature (P = 0.620 for the right eye, P = 0.918 for the left eye, for the total group, Figure 3(b); P = 0.686 for the right eye, P = 0.620 for the left eye, for the young patients, Figure 3(e)).

The CAA value decreased with the abrasive wearing passes increased and had a

linear correlation with their abrasive wearing passes.

The first one assumes

linear correlation between spring discharge and water level difference [Q.sub.GOLUBINKA](t) = Km-m and the second assumes nonlinear correlation [Q.sub.GOLUBINKA](t) = [K.sub.m] x sqrt(m).

A weak negative

linear correlation was found between participant age and the anteroposterior diameter ([r.sub.s]=-0.15, P=0.02) as well as participant age and the transverse diameter ([r.sub.s]=-0.14, P=0.03).

Men had higher mean pericardial fat volume than women and pericardial fat volume was found to have a

linear correlation with increasing age.

The

linear correlation coefficients of DESFC growth rate at 10 given characteristic DESFC sizes for the above 7 distributions were given in Table 2.

From the

linear correlation analyses of the average T and RH (Fig.

The Pearson's

linear correlation and the stepwise linear regression model were used to investigate both the relation and the prediction between variables.