Table 5.
Regression analysis for the dependent variable wood yellowness (Y).
| N = 24 | Regression Summary for Dependent Variable: Y R = 0.9866, R2 = 0.9733, Adjusted R2 = 0.9708 F (2.21) = 383.06, p < 0.0000, Std. The Error of Estimate: 1.3641 |
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|---|---|---|---|---|
| b* | b | t(21) | p-Value | |
| Intercept | −5.7726 ± 0.7337 | −7.8675 | 0.0000 | |
| L* | 1.1630 ± 0.0537 | 0.6633 ± 0.0306 | 21.6611 | 0.0000 |
| b* | −0.2555 ± 0.0537 | −0.2388 ± 0.0502 | −4.7595 | 0.0001 |
| N = 24 |
Regression summary for dependent variable: Y
R = 0.7141, R2 = 0.5099, adjusted R2 = 0.4364 F (3.20) = 6.9361, p < 0.0022, Std. The error of estimate: 5.9908 |
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| Intercept | 23.7871 ± 3.6857 | 6.4540 | 0.0000 | |
| Yi(Ac) | −0.6029 ± 0.2488 | −0.0810 ± 0.03343 | −2.4238 | 0.0250 |
| Yi(Et) | 0.0597 ± 0.1978 | 0.0080 ± 0.0264 | 0.3022 | 0.7656 |
| Yi(Et-To) | −0.1702 ± 0.2786 | −0.0214 ± 0.0351 | −0.6109 | 0.5481 |