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Table 8 Regression analysis of the heavy metal content of the samples

From: Data analysis of heavy metal content in riverwater: multivariate statistical analysis and inequality expressions

Model summary
Model R R square Adjusted R square Std. error of the estimate Change statistics Durbin–Watson
R square change F change df1 df2 Sig. F change
  0.836 0.698 0.640 132.18065 0.698 11.956 6 31 0.000 0.863
ANOVA
Model Sum of squares df Mean square F Sig.
Regression 1,253,384.434 6 208,897.406 11.956 0.000b
Residual 541,623.431 31 17,471.724   
Total 1,795,007.865 37    
Coefficients
Model Unstandardized coefficients Standardized coefficients t Sig. 95.0% confidence interval for B Correlations Collinearity statistics
B Std. error Beta Lower bound Upper bound Zero-order Partial Part Tolerance VIF
(Constant) 589.675 131.363   4.489 0.000 321.758 857.593      
Ba 8.814 1.608 0.694 5.481 0.000 5.534 12.094 0.736 0.702 0.541 0.607 1.647
Cr −51.508 16.046 −0.335 −3.210 0.003 −84.234 −18.781 −0.083 −0.499 −0.317 0.893 1.120
Fe 0.097 0.252 0.048 0.386 0.702 −0.417 0.612 0.387 0.069 0.038 0.640 1.561
Pb 201.610 424.407 0.056 0.475 0.638 −663.974 1067.194 0.338 0.085 0.047 0.689 1.451
Sr −6.082 37.166 −0.020 −0.164 0.871 −81.882 69.719 0.275 −0.029 −0.016 0.680 1.471
V 16.486 8.954 0.251 1.841 0.075 −1.776 34.748 0.509 0.314 0.182 0.522 1.916
  1. aDependent variable: Sb.
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