Regression analysis of the CSLs
| Metric | CoT | CoP | |||
|---|---|---|---|---|---|
| Triaxial compression – 86S | Triaxial compression – 91S | Triaxial compression – 95S | SS | Unique | |
| Slope (b1) | 0·9650 | 0·9703 | 0·9826 | 1·0357 | 0·9504 |
| Intercept (b0) | 0·0585 | 0·0469 | 0·0269 | −0·0548 | 0·0831 |
| Standard error for slope | 0·0715 | 0·0705 | 0·0904 | 0·0528 | 0·0423 |
| Standard error for intercept | 0·1189 | 0·1138 | 0·1425 | 0·0838 | 0·0719 |
| Multiple R | 0·9919 | 0·9896 | 0·9835 | 0·9873 | 0·9733 |
| R² | 0·9838 | 0·9793 | 0·9672 | 0·9747 | 0·9474 |
| Adjusted R² | 0·9784 | 0·9741 | 0·9591 | 0·9722 | 0·9455 |
| Standard error | 0·0074 | 0·0044 | 0·0027 | 0·0101 | 0·0156 |
| Degrees of freedom – df | 3·0000 | 4·0000 | 4·000 | 10·0000 | 28·0000 |
| F-statistic | 182·2143 | 189·2746 | 118·1156 | 385·0804 | 503·8828 |
| p-value (F-test) | 0·0009 | 0·0002 | 0·0004 | < 0·0001 | < 0·0001 |
| Regression sums of squares | 0·0096 | 0·0035 | 0·0008 | 0·0428 | 0·1164 |
| Residual sums of square | 0·0001 | < 0·0001 | < 0·0001 | 0·0011 | 0·0065 |
| t-statistic (slope) | 13·4987 | 13·7577 | 10·8681 | 19·6235 | 22·4473 |
| p-value (t-test) | 0·0009 | 0·0002 | 0·0004 | < 0·0001 | < 0·0001 |
| Metric | CoT | CoP | |||
|---|---|---|---|---|---|
| Triaxial compression – 86S | Triaxial compression – 91S | Triaxial compression – 95S | Unique | ||
| Slope ( | 0·9650 | 0·9703 | 0·9826 | 1·0357 | 0·9504 |
| Intercept ( | 0·0585 | 0·0469 | 0·0269 | −0·0548 | 0·0831 |
| Standard error for slope | 0·0715 | 0·0705 | 0·0904 | 0·0528 | 0·0423 |
| Standard error for intercept | 0·1189 | 0·1138 | 0·1425 | 0·0838 | 0·0719 |
| Multiple | 0·9919 | 0·9896 | 0·9835 | 0·9873 | 0·9733 |
| 0·9838 | 0·9793 | 0·9672 | 0·9747 | 0·9474 | |
| Adjusted | 0·9784 | 0·9741 | 0·9591 | 0·9722 | 0·9455 |
| Standard error | 0·0074 | 0·0044 | 0·0027 | 0·0101 | 0·0156 |
| Degrees of freedom – | 3·0000 | 4·0000 | 4·000 | 10·0000 | 28·0000 |
| 182·2143 | 189·2746 | 118·1156 | 385·0804 | 503·8828 | |
| 0·0009 | 0·0002 | 0·0004 | < 0·0001 | < 0·0001 | |
| Regression sums of squares | 0·0096 | 0·0035 | 0·0008 | 0·0428 | 0·1164 |
| Residual sums of square | 0·0001 | < 0·0001 | < 0·0001 | 0·0011 | 0·0065 |
| 13·4987 | 13·7577 | 10·8681 | 19·6235 | 22·4473 | |
| 0·0009 | 0·0002 | 0·0004 | < 0·0001 | < 0·0001 | |
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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