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Regression - using R

Regression


The R output for the regression analysis is:

Analysis of Variance Table Response: scc Df Sum Sq Mean Sq F value Pr(>F) log(pha) 1 948443 948443 9.5577 0.03652 * Residuals 4 396934 99234 --- > #Obtain coefficients > summary(model) Call: lm(formula = scc ~ log(pha), data = vetriv) Residuals: 01 02 03 04 05 06 -241.7 -246.3 189.2 429.7 -221.7 90.9 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 332.6 133.8 2.487 0.0677 . log(pha) -629.3 203.6 -3.092 0.0365 * --- Residual standard error: 315 on 4 degrees of freedom Multiple R-Squared: 0.705, Adjusted R-squared: 0.6312 F-statistic: 9.558 on 1 and 4 DF, p-value: 0.03652