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, .:•d _~] ~~ _, ... .•, <br />,:, i .: n': ;~i•: cis ~: i~.:: .. .,. . . c ;c ~ ,.~. <br />c•: <br />....,,.._ ;ctau'.~- r:~,rtt~~icn rya rc•~~t•~~rt:~tct'. :: r. :.. .~. tc5 tL~~ pt,cict~.: ~ ,. •ion <br />._~ t:~~e r,ade] as eitr.:n in the fe~]]c~•~in6 l,~~Tnthrtica] cc-.aari5on: <br /> <br />Sear <br />1 2 <br />x z <br />l 2 <br />]. Reference area (x.) 55 50 <br />i <br />2. Re~•egetated area (}•.) 50 55 <br />i <br />1-ne data from the reference area can be used in the model developed from the <br />pre mine data to "predict" what 90% of the standard for the reclaimed area is: <br />}• _ .9 (Bo + 61xi) _ .9 (-22.143 + 1.439 xi) <br />]'r. 1 y = .9 (-22.143 + (1.429) (55)) <br />j• = 50.8 <br />1'r. 2y = .9 (-22.143 + (1.429) (50)) <br />y = 44.4 <br />An acceptable lower bound on the error of prediction by the model can be calcu- <br />lated by the following equation. <br />_ -)2 <br />}' - is ` 1 + 1 + (xi - x <br />n __ <br />- r: <br />where: y = predicted value for the revegetated site from y = 80 + Blxi <br />t = one-tailed value from the t-distribution table at a 90% confidence <br />level with n-2 degrees of freedom. <br />s = estimate of the standard deviation of the random error in the model <br />n = number of r.i or yi samples used to determine the model, four in this <br />case <br />4-108 <br />