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Errors-in-variables Regression - using R

Errors-in-variables Regression

The R output for the regression analysis is:

 Analysis of Variance Table Response: log10(tec) Df Sum Sq Mean Sq F value Pr(>F) log10(adl) 1 1.44278 1.44278 54.181 0.0007268 *** Residuals 5 0.13314 0.02663 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > #Obtain coefficients > summary(model) Call: lm(formula = log10(tec) ~ log10(adl)) Residuals: 1 2 3 4 5 6 7 0.01252 0.01482 -0.07420 -0.22635 0.03385 0.27172 -0.03237 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.8235 0.3397 8.313 0.000412 *** log10(adl) 1.5383 0.2090 7.361 0.000727 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.1632 on 5 degrees of freedom Multiple R-Squared: 0.9155, Adjusted R-squared: 0.8986 F-statistic: 54.18 on 1 and 5 DF, p-value: 0.0007268