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Brian T. Frus ® Page 3 of 3 <br /> Pacific Environmental Group <br /> Project: 310-01.04 <br /> Febraury 1, 1993 <br /> LINEAR REGRESSION OF VACUUM DATA <br /> ax <br /> covert an equation of the form Y = e + b into linear form: <br /> Ln(y) = ax + Ln(b) <br /> Plog = ln[Pave 1 0 <br /> i L iJ Plog = -5.335 <br /> -5.805 <br /> Calculate the slope, y - intercept and the correlation coefficient: <br /> mPln := slope(R,Plog) mPln = -0.262 linear regression slope <br /> bPln intercept(R,Plog) bPln = -0.951 linear regression intercept <br /> rPln corr(R,Plog) rPln = -0.88 correlation coefficient <br /> Plot the field data and the regressed curve in semi-log form: <br /> r 0 . .100 <br /> 1.0 1.0 <br /> 0.1 <br /> (mPln• r+bPln) <br /> Pn ,e <br /> .O1 <br /> 4 <br /> 0.001 <br /> 0 R ,r 100 <br /> i <br /> Calculate the effective radius of influence at 1% of total vacuum: <br /> ln(0.01) - bPln <br /> Re :_ Re = 13.96 Feet <br /> mPln <br />