Table 6.

Regression analysis of the CSLs

MetricCoTCoP
Triaxial compression – 86STriaxial compression – 91STriaxial compression – 95SSSUnique
Slope (b1)0·96500·97030·98261·03570·9504
Intercept (b0)0·05850·04690·0269−0·05480·0831
Standard error for slope0·07150·07050·09040·05280·0423
Standard error for intercept0·11890·11380·14250·08380·0719
Multiple R0·99190·98960·98350·98730·9733
R²0·98380·97930·96720·97470·9474
Adjusted R²0·97840·97410·95910·97220·9455
Standard error0·00740·00440·00270·01010·0156
Degrees of freedom – df3·00004·00004·00010·000028·0000
F-statistic182·2143189·2746118·1156385·0804503·8828
p-value (F-test)0·00090·00020·0004< 0·0001< 0·0001
Regression sums of squares0·00960·00350·00080·04280·1164
Residual sums of square0·0001< 0·0001< 0·00010·00110·0065
t-statistic (slope)13·498713·757710·868119·623522·4473
p-value (t-test)0·00090·00020·0004< 0·0001< 0·0001
Note:

Triaxial compression: triaxial compression test; SS: simple shear test; Meaning of regression metrics: Multiple R: Return the correlation coefficient of the data sets; R2 (coefficient of determination), proportion of the variance in the dependent variable explained by the model; Adjusted R2: R2 adjusted for the number of predictors; compensates for small sample sizes; Standard error: standard errors for Y estimate; df: degrees of freedom is the number of observations minus 2; F-statistic: Tests whether the regression model explains a significant amount of variance; p-value (F-test): Probability of observing the F-statistic if the model had no explanatory power; t-statistic: Tests whether an individual coefficient (e.g. slope) differs significantly from zero; and p-value (t-test): Probability of observing the t-statistic if the coefficient were actually zero

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