frtr - Peoria County

Transcription

u"',
]Adj ustect
N: I $ultiple R: 0.656 Squared rnultiple R:
aquared nultiple R: 4"336 Siandard e:rur of esti.mate: 0.S06
CONCENTRATIO
Coefficient
Std -:ror
$td Coef Tol-erance
4
0.0
0.085
-0.656
Analysis of Variance
2.2'?
-0.183
l?
-Sq'Jares DF l,lean*Square
S-':tt-of
1.669
z, tutJ
Xi:::i
ry*
Ge
Ge
$I;\I{NING
1
1,669
b
0.368
L
.0$0
F-Ratio
p(? Tail)
t
5.
-2.
0.43L
354
131
0. 002
0.0?i
E
{.54:
0.077
{Studentizfd Reeidual. *
(Studentlaed fr.esidual =
-2.203)
***
88 is an ou'ilier
89 i.s an cutlier
?.102)
Stati,stic
3 . :l 60
Lrst Order Autocorreiaiion 0.606
G folloninr resulls are for:
* Gi 95
?iSLLS
Surbin-Sat son D
Uarr CCNCENTRATIO N: I
Multiple R: 0,801 Squared r'.ultlple R:
ulted squar*d multiple R: 0,58? Standard *rfor of eetiaate: 0.691
Coefficient
Std Brror
16.461
2.593
0.098
T;;,
-0.321
SLd Coef To,lerance
0.0
-n
nn1
si Variance
,*Squares Df t4ean-Sguare
3. 133
1
5. 133
?.86? 6
0.478
1
.000
0,642
t P{2 Taili
6.348 0.001
-3.2']7 C.017
R'ral"ysis
ll*,..
Sum-
m::-:
F-Ratj"a
10.741
H
0.017
2.3?9
Brrbin-Satson D stir,istic
fnst Order Autocorrelat ion -4.256
I
tTe followinE results are for:
nsit$
I
In Var:
-
G20s
S Multrple R: 0.0?0 Sguared nnrltiple R: 0.005
R: 0.0 $tandard error: of estimate: 7.979
f*nrfficioni
Std Error
Std Coef Tolerance t
P(2 TaiL)
29 .Sl7
20.406
0.0
0.682 0.521
l" . 129
-0. 195
1 .000 *0.1?3
-0.0?0
0. g68
CONCEIITRATIO N:
Adlusted squared multiple
I
*n,
gTR
Analysis of varia:rce
il"",.
s
***
ilr*
Sun-cf-Squares Df'
1.906
381"594
regSron
lduaI
glAIlltING
I
E
r*r
t01 ie an outlier
I
6
Mean*Square
L.906
63.399
f-Ratia
0.
c30
(Studentized Residuai *
P
0. 868
5.330i
1.973
E[rbin*Watson D gtatislic
Eitei Order Ailf.oqorralation *0.044
n
tra
foilc$inq rssults are for:
o c21S
E wr,,r.r.e
*sxgr
-
r
PEIjusted
-gff,sct
frtr*'
$: I Multipis Rr 0,303 Squared nultiple R: 0.092
squarec.l multiple R: 0.0 Standard error of eeti.nate: 1.159
Crd
Frr^r
Std Ccef Tolerance
Coefficient
t P {2 Tail}
4.343
11.496
0.0
2.644 0. 038
0.16{
-4 I ?a
-0.303 1 .000 -s.779 0.466
CoNceN?R&?I0
S*Hatio
0.60?
0.466
foJ.lawlnE r€sults aro for:
!r I{uI,i$
I
= GZ?s
r
T
:'jp vaij coNcgNTRATlo N: I MuLtj.ple Rr 0.459 sauared multipre R: 0.210
sguared multiple R: 0.079 Standerd error of estimat.er 1..302
fi,r"tu.f
Coefficient Std Error
*.*a
Std Co€f Tolerance r
P (2 Taill
12.023
4.8ri3
0.0
.
2.462
0.049
*0.233
0.184
s*'*'
*0.459
t. vuu
-1. zb5
0.2s3
Surn-of-Sguares DF Mean-Square
f:::","',
Residual
2.114
-tu,
1
rb)
StatisLi.c
Crder Autocorrei.aticn
1.599
1"694
I* BAANING *ro
fttse
1.?2 is an outlier
Lrrbin-Watsorr D
2. ?10
f*Ratio
(Studentize<l Residual
P
0.253
=
2.185
-C.296
fst
the f*ll"or.rinq result$ are for:
* G23S
tSET-t$
: C0$CENTR.S,fI0 N: B Hultiple R: 0.695 Squared nultiple R; Q .483
Adju$ted sguared multiple R: 0,39? Standard erro: of esti$ratei 0.9?4
Coefflcient Std Error
$td Coef Tolerance r P{2 Taii)
*;;.
15.609
d ?qq
3.280
0.0
0.003
"0.293
Q?R
I
o
"L24
-0.
695
:.
0.056
0c0
Su&-of*Squares DF gean"-$g1}are F*Ratio
Source
4.289
4"586
Si:,,i"-
1
4.?99
6
0
,
5.610
r
0. 056
1164
o*:_^
l* isA3tsI$o 130 is an outlier
I8"
f .i48
ffirbln-slatson D Statistic
girst Order trutocoxrelation *0.005
{Studentized ResiduaL
-
z.25f3t
I-e foLlo*incr results are fc,r:
* G?4s
- $nil.$
Multiple Rr 0.150 Squared muleiple Rr 0,023
Pgp Var: CONCENTRATIo ll: I
'E
lfiu*tea squared rnultiple fi: 0.0 Standard err:or of estimate: 0,i?l
Std sr "'o:
Pl? ?;il!
coef f icienr
Std Coef Tolerance c
Sff,ect
"r
2 "t41
0.0
3. d06
$. sl4
INSrAll?
"293
0.081
-0.030
-0, 1s0
I .000 *0. 372 *."72'J
.-,
Ana.l.ysls of Variance
r--_-Sum-ot-Sguar€s Dl' Mean*Squdre f-Ratio
!
Da^/ae
e i
h 1.]L
0.045
:.
$. fl45
0. r3s
^n
1.955 6
0.3?6
.I
I
lEbin-Rat eon D Statlstlc
2.082
Fif6t, orde r Autoc$rr€Iatisn -0"182
I
I
F"C
I
I
t
I
I
I
I
;
T
r
I
t
l
ILOBIDE, DISSOLVED, REGRESSIOI{ VALU0S FOR Ln oF CONCSN1RATIOIT
rI 913 At'lD Gl{ DID NoT cttAN68, r}lus, No R.gg&r:;ii;t$ r.}tatr;-i.$ sAg pERr*Rurs
r GO{S, 6085 AND CIOS HAD BEEN SSMPI,SD LE$S TIiAS 8
SUANTER$, IHUS, HS R*GRSSSIS},I
I
Iry-lol.rowtng results are fori
trt$
]r- var:
-
602$
N: I Mult,iple R: 0.13? $qualed multipJ.* R: f.&1"*
trljust"c squared murriple R; 0.c standard errar of sstinats: 0.Osq
coef ficient
litd grrar
std csef ?olerance t p{? ?ei1}
lfect
1.86?
]iSTAI']T
0.L84
0.0
10.1{5 fi.[0(}
0.003
QgR
il.00?
0.13?
1.000 0"t6a 0.?a3
Anelysls of Variance
Ir
lFurce
Sun-of-sguare$ Df Mean*Sqriare f*&atic
f
INCoNCENTRAT
000
0.021
[gression
iduar
|s
D---------
0.
1
?
0.0C0
0.
]34
0 " T?5
0. S03
*** ly3;llflNc **r
4 i.s an outlier
{Studenti?ed R**.i"dual. * *3.96!5{S*il?;
I!*u
trbin-I$atson $ Siati.sric
2.296
Fisgt Order Autocorrelation *0.16?
follcwlng t€sult.s are for::
le s.€i,Ls
* 603s
f
Dep var: tl':coblcsNTF3? ltr I
uul.tiple &,: 0,{j3 squared murtip}e &r *"18*
!3ueted sguared multiple R: 0. 053 Standard error 6f e$tillr&te; S. l"S?
T
Fgfeet
Coefficient
Std Error
2.275
0.4{r0
0.018
U. UI)
Std Ccsf fcl.er*nce
$.0
0.433
1.000
f
Fi:
jd!t/
s. 6*q
0"frs1
f.
1.i?8
?&3
AJiallsis of Varianse
Surs-of-Squares Of Mean-$quare
f"&at !o
n n16
1.3S8
il::::",*"
0.016
0.068
Rasidlral
1
P
n :;t1
0. 011
t
bu.rbin-gatson D Statistic
7.648
fir$t Crdirr AutoeorreLation *S.4?3
I
are for:
!e fo3"lovi$g rest.rlts
* G{i5S
t llEtl.$
lfp Var; I"NCONCSHTRAI N: I t{ulLiple R: 0.t38 Squared mu}riple }tr f.i44
I
13r ,teO squared multipl* R: 0.{68 Staltdard err*r of esti-elele t *.\?"t
Sffect
Co€fficj"ent Std grr{]r
$t.ci {*ef T*ler*n*e
r p{? y*::i
!
2.?0E
0.4?E
f"0
3,&&3 t3"*fr1
II6S}ANT
rD
*s.?38
-0.s48
0.0i^s
1.&*0 *7.&1& *.*3?
Anr'l
rro i e
^f
Urri
a!,-a
trce
S',rlrr*of-Squares DF
Sggresslon
0.116
T
fr"11tt
0. c99
6
0. 0:.6
aidual
Medn-Sqi.tare
f-Aetio
I - ltit
F
fi. s31
Srn*Hatson s gtatistic
i,893
IFFOrder Autocorrelation -0.C81
* f,ol"Lgwing results are for:
* G065
3igl"t'$
Io Var:
I
I.NC0blCS}lTR.e?
$:
$
i,lrrlt:pIe R; 0.]60
Squareo ruitrple
F: r
:.
A$IAI.YETS
ts*,s pc&.g*fr,xgs
t€d squafed
feet
$ultlpls *l 0,0
Standard
Cs*f,f,iclent
gtd gr.f,or
2.239
0,33$
0,013
*0. 01?
error sf sselmatst 0"SSd
Stcl Co*f T6]'+rat1 *
r S{3 tsi.l.}
0.s
,
{,s$1 *.fr*l
*0.350
I ", 00 **.9d5
*.3sx
Analysi$ of Variance
H:
$um*of-$quares 0f
0.006
0.054
RB,$idual
t.
aARNING
Hean-Sqr_msg
g-X.dt 10
t
v. uvo
0. *6s
0. s93
6
fr
"1t* I
*i*
is an outlier
*}"3dti
{$tudentized Rssidual *
3.107
lrbrn-Watson D Staristic
Ir$t Order Aulos.orrel8tiorr -S,603
'llro fpllosing resuLts are for:
n vl€I.L$
- G0?S
r
I t*"t l,NcoNcEl{TRAT N: 9 Multiple R: 0"?6s $quared $'rrir}t}].s s: s"?*t
AdJust6d sguared multiple R: 0.532 stand*rd errcr sf, e$timdt.€: s,*ss
r,
Coefficient $td Arror
Itect
$rd {sef ?*lsran*4
{
P {; g&Jr} }
-coHs?Axr
L.924
*"c1
3.*5?
*. *ls
0. 041
U.UIJ
0. ?6&
l . sils
J. 1is
* " i]:.6
gaFe
28
r
Analysis Gf varia:tre
$r:m-of*Squares Of Mean*Sql:ar* f'*Ratis
Source
0.100
0.069
*;:n1,'"
I
0.1*s
7
0. *1.0
l':-g&R$11nJ6 *o"
.12 is en outl.j.er
E
OucbLn*{atson
P Statistic
2. ?n?
- t Cfrder Autccof,relation
*A, "7t 3
ll
3S.$3S
*
{Studentited &esidualL *
"
il;s
i . t")a,:
folloning re*ul!s ate for:
= itl 1c
WEI,I,$
Irp ?ar: lNc0llcgl.]?nA? $: I lduitj-pie &.: S.S*$ gqtrassd $r}l"e;pl* &r *.*4*
f
Ijustsd rqr:ared multiple R: 0.9SE $tancierd *rxr:; of, estlffiri*s: {i.fi4?
Ef,fe*t
C$ef,fisiefit
Std grr*r
q p{? f,iArir
$tC Cff*f ?*lerance
I.
fr***,
0.t65
JJ1
q.*?3
P"*
fi.8S$
s. ${i?
7"tt33
*.3XX
:.***
il"!;i)i)
t"{]is
&n&l"y*is *f Variar:f*
l-'.-
$um*of,-Squares pF. M€en-gq*sr*
Regr€ssi6r1
0.027
0.015
lsidual
s.
6
f
*;?
-li&{ i0
P
:r"4ii4
rj .
#. *$?
*i&
I3b---e*"*
I
Durbin*!9at$on D Statisf,ie
Order Autocorrelaiion
IIfst
llle f,oXlot*inq res*}!s ere f*f
* G12q
?ar:
3,1'lC0FCXNtfi.&T
l{r I
sql:ared:&ulEiple
eoefficiect
nlFn
1,809
-U.Q82
t
l{ulrtg:le
R:
F:
iLsrruaru
,(itcl frrnr
C.'-c..'j
e,5 :tr:Jr t
qt-
r..
*"*
U"tlJJ
Arirluer
s
r,t
{"r-t
-':.i'.iJ
r/;vrrn..-
ft: t " i*.ir
I G{-ir rFld
ez: Ja v!
$'fi??
i.*s3
-8 "*84
Jq-,:r.
L.-'.
- (.,
'r i lq
i,
-,
1.
J {t{
.t
l.*
i;
Y6;";
;
iri!
I 'iri{
Sum*of*$quares
I
-rrco
- 6grarslon
R
Rc$idual
DT
0.001
0.3?8
l{qan**qusr*
f-&st.to
0"s01
0,01s
I
tt
*, *ss
0. s$s
G'qr-*6*+4eL
url:-watgon
ffl;order
]
-
Au
Sratistic
tocorrelation
D
foiloring re$ult$ are
* GISS
t{8Lf,$
2.4s7
*0 349
"
f,or:
var: LNcolrcElIrRA? $r I uurtipl* R: 0.0*'f $qr;arsd rrrulri,p:s &; *.***
ljusted sguared multipre &: 0,0 $tandard srror of s*ti;Eatel s,frgt
Eff,ect
coeffirieBt
std error
std csef f*ler*ncc
* s,{* ?eii}
r.6?4
0.341
o"*
{.stp s"**j
$srnNt
]I
0.s03
!t:3
0.0i3
*.oil?
Analysis of Var$erice
gu*r-of*Squa{e* nF, !6een*$qu.&rs
l[,"*
Rsqre$sion
0.
0.
sr:::
s00
049
I
6
t,0s0 *"*x3
f*Ratl*
p
0,045
* " *$r]
0. s0*
s.s}$
*.*3*
2-6ga
Elfbin-HaEson D Sratisric
Order Autocorrelation -0.391
lrst
ilu
tof
ro*ing results are for:
* Gl5$
$S1,lS
ilultipls 8: 0.5F8 $:{usred mi.ri"f rpl* fr: * " }&6
trdJusted squared multiple R: S.?3? Stand*rd *rr*r *f ssqimats; *,1"*f
Coeff,icienl $td trrror
p{; yetii
$td Co*t ?*J.ere$a*
f
var: LSS0NCEII?RAT l.l: I
n,
?
.dnc
"0. 0{1
Qts
n cr n
*, *23
E "tt':
L
"# " $8S
**fi *, ?s}
*.
"
1"*9
An€lysi.F af, Varj"ance
t**..
su$*of
llliiii::
*
*6
-$quares $F !{e&rx*Sqrrar*
0.084
l.
fi. *84
0"158 6
fr .426
1*
3. 1?4
S'*t{et
S
*
"
:**
H;U{tillt{G r * *
C1
:-
--.
tJLUse0r-J 3eJ -r@5-'fua j
^,!#ri,=-
4 " i$fi1
e
Sratistic
l.d60
F'lret Srd*r Autocsrrclation *S.fS,
are for:
fe follo*rir:g xesults
* Gl?s
I t{ELt{
n-Ifat$on 0
}l: I MilLtiple lir *. {rrl, sqx*r*d }H*J.riple }i.r fi, #*3
multiple F.l 0"0 $ta|}dard err;r *f s*r:Lr*a{*r *,S$tr
ser) vagr 1$cobl{g}iltrRAf
I
IJuBeed *quared
gff,€et
fno€Fiaianr
lvsr.alrrr,L
$ste*t
I.*,*
CFd
P--^JLU
&ltu!
2.',7fi3
8.0*2
-.-.gf
*.34A
*.{}
0.s13
*"fis:
Analysi* *f V;iri*rr:e
*Sgu*r*s
9r:"4-of
nf !,!*an-5qr:*r*
0.00*
I
*"$*s
&.0c9
6
#. s8*
$tatistic
7 ?1c,
El Ord*r Autocorrel*t:sn -S .;&6
followjng resulrs are tor:
O$sb*n*Wats$n D
:lLo
la,:€ld!,Cc
1.***
P-S.&f r!.*
*.*t&,
t
k -,
} _*$k
*":it6
tt
1J"3fr[
:
+"
-
*"fri;
i;,&t:A
J*"ort
Dep Yar:
-
G18$
INC0}ICEI{TnR?
N: I
Uulripls R: 0.S{S
0"4ii
Sguarsd urulti"pl* &:r
0.3?5 Stdnd€rd err*r of, s$t{met*; fl,*&S
Coef,ficient Std grrsr
$td Csef Toler*nee t F{} t*Jt}
?. 665
0. 3;3
0.0
8 , t4?
*. S*{}
-0.0?6
0. $rt
-0. 649
1 .0S0 *9, $9r
* " **t
nuJ.tiple Rl
Equared
fl-ancr
D
r'
-
Ana:ysis of Varience
Su$-of*Sguares DF Mcan*Squere F*Retto
t:::",."
3es*dual
0.032
*n*rn
f.oo*'*
t
0.0{$
0.032
*.
4.3't2,
0.007
6
," an ouf,r.ler
v
(Studentieed Resi.dual *
**;
-u. {*3}
3.184
LFbin-fiatson D Statistic
fst Order Autocorrelati.on -0.622
-
-he f,ol,losj.cg results are for:
T
I
*
$g!I.$
6195
var: LNCONCEITTRAT N: fl ltuiciple R: 0.797 Squared multrple .q.: ,;.rJ:,
J]
*
&djusted squared mill"tiple R: 0.5T{ $tanderd *fr{}r e,f *stir*a**r fi.004
Coeffici.ent
3.S89
-0.019
*n,
geR
Std
Brro{
0.316
t.01?
(*6f f,*}esance r p{? T*iti
0.s
3.??3 #-*#*
-fl.?g? 1.S0* *3.33i *.sls
Std
of Varj.ancs
$rim*of,-Sqilares Ff Hean-Squar*
0.0?4
I
&. S?4
0.043
6
0 .00?
l'
A"naly$is
ffo1rrae
ffii.:
p*&.&tgs
s
t0 " 44?
*.#1S
?.3't6
lrbin-gat.son D gtatistrc
Irst Order Autocorreiati.on -$ "235
Tbe fplLo{.ring resu}ts ax* tar':
= G2cs
A wELl,S
* uut, LNCCNCENTR&f !{: A Ftutttpi.e F,! t.03{ $qu*ra*i rnrrt"ript* Hl,J.il*i
ndJu$t*d $quar*d Nultlple F.r 0.0 Srarrdard **rr:r cf Gsgitri.**sf *"4;i
foef,ficient $td grrels $rd *e*f ?ol*s*;r** t &{; y*r}l
*..,
7.3L4
0 " 005
cst'r5?s$t
r
*.*
*. *34
of Variar.r*
$rrln*of -$quares Sf Mearr-Sqdare
er"0$1 I
*"S$*
)'
"
S**
x"*3;
*S;
(}.
*.:,-t{i
*. b}}
Ana).ysis
$plrss*
*m:l*
s.
1.639
fi.{}6?
1,145
I{AtrWlfiG ** *
101
ls
6
Q
tr*Ra*i4}
v
*.**?
$" $*?
" \tt
{$*$d*trt.iesd &seld*ai *
an sutl-ier
3. &5* i
r,dts
fi $ietisiis
t fxd€r Auto*off€ist!0n 0,S3S
fsllouing results ax* tart
Fucb
Fucbiq-Aais0n
t.
^fl,LS
pEr:
-
-
GZLS
$uitipie R: 0"Ziio Jiluored F,uir r.plE y. J -6:
DjUsbeqi squared &uitrnla u' n f) (iih'idrd cf dor v! €sf rrh4te: U. {{,t
LNCONCEN?RAT
l{: I
{seffrrie$t
ffn,
2.41n
St.l [rr0r
0, $3$
5t:i CLtrf T.,Jcl.nte
&.#
I
Fi;
&.{i1t
j@j:i
{j"f0}
-0
"
015
0.
020
1.000 -0.?3?
-0. ?sc
0.it89
Analysis of Varisne*
Sws.of-Sguares Df Hoen*gquare
h
At r
v.vl.l
0.1e0
t
0.ff11
6
0. s?0
s
S'-Ilati0
0. $43
s" 46s
in-llatson D $tatistic
t.?61
!'lsdt Ordex Autocoffelation *0.004
a
* f,o]]oring results aro for:
I ger-r$
r
liusted
*
{izls
!4rp Var: LNCONCENTRAT N: I
J
$quareci muJ.tlple R:
Coefficient
[f,f,act
Regrgssion
t';;;;
Casa
I
[dultiple Rl 0.488 Squer*d flu:t1p:s Rr
0,11? $tandard er**r erf s*timager fi"f;S3
{3.*33
hrror
$td {**f ?*l*.ran*E t fli} yesii
3 " 11.0
t.003
0.s
3"*S9 *"*f1
-0.0$2
0.038
-0 " {*s
1.0fJ0 *1 ,3?} * " 31S
Analy$is +f Variane*
Susr-of,*Squares Sf H€dn*Sq$ss*
g'*Nat.i"s
p
s . 1.34
I
0.334
t"ss0
*"t1*
StC
0.429
s,07a
I22 ie an outlier
iStr*ei€$tlsaei E*sidsal
*
*4.;4Si
?.80$
Irbin"Hafsan P gtatistic
Fst O{der Autocorrel.ation *0.240
Ths fcllosinE resuJ"t$ are f*r:
I-sj,Is
- G23S
E
il$r:
N: B rfutript€ F: 0.6?6 Squared m*.t*gpl€ Hi g.gS?
sguared nu}tiple R: 0.366 $tand*rd error of ec?iraar*; 0_}SS
fi{lusted
I
coef ficient
$cd error
$td c$*f ?;lerans*
r pi; ?#i.5i
lfect
I,NCONCSbIfRAT
cil{srAN?
ru
*.At}"t
0. 0t I
2 "96't
-0.035
I
Igreesior:
Gisue:
tr .
$s0
?.
*3
.
3S}
?4?
$un-of-$quares nf Mqa$-$qilaxe F-&&tiq
0.060
I
S"SS*
S"S4S
f .0?1
6
s. *ri
T
tr* $IAR$IISG *r*
130 iE dn outliflr
lBe
0uabin*gtafscn D Statistic
1.6SI
lrst Order &r:tocorrelatio& *0.049
I
Ie f ol lor.rino resul ts are f or:
* S?4$
9*9X,I,9
var:
*
6?5
"$.
*.
***
SSS
AnaLy*i.s at' Varians*
;
$ourss
f
ftu*t.a
{t.
_{J.
LNcoNcstErRAT 1l;
squared InultiFle
X:;;,
n
fii:ii::
I
Coeffic*ent
1.991
*0.0$g
S.***
($tud*ntie*d Fecidx*! *
Multiple &: 0.i5*
&: 0.{i
?
SLandard arEsr
$ld Error
x, }tl&
sgli*r*d m**.*iple &r *"*?3
*f es{ir*disr S"*S*
Sed Co*f
ysler:nn*e
q
F{? g*{i}
0.330
0.C
6.trr!
*s"15{i
0,8\2
t.*fiil _*.3\tk
Analysis 0f Variat}es
B
Sum-of -Squares OF Hean-Sr{uare F-Fa.,:o
0.$s1 I
U,
USb
t)
]
*"**x
s. *fi8
s"tls
ft
a*?
, -{:
S"?}3
ln*flatson D Stati€tlc
first
t
I
I
I
I
t
t
t
I
t
I
tr
Order Autocorrel,ation
u.08?
-0"1s?
I
CYANINE, TfiTAL
l
I
0.020
'Concsntr*tionn dstsrynined ts bm be*ffifir tf?s
detecti*n levef were estimated es twif d tfr*
deteetion lev*l fsr nl| sl,ati*ti*fr| purpm*e.
t
ct)
I
-
0.015
E
r--
o
at
*t
il
I
t
{s
trl*a
0.010
r,
0)
(;
g
o
(J 0.s05
il
I
il
t
'-!f
I
t
I I I J I, i,i",.,,i,*L, t*l
n
v In
v
#j .6.-6.-4
.q
^gt
^4 ^6 ^q
.'1"-L,|.*,&*J*-.$.*.{**,$,*,I.**L_3 ",*
^6.^(e ^fl .6! -f4^c.. *c.. ^cq ..€!
^#a
^(q ^f^,f*
s$''s$b$6$Eqts-drylTltltl?}?}:*?l'k}bTpWlpgry.-
M*n*tsrin# F**n*
I
I
T^T
T
I
I
I
I
t
t
b
t
t
t
t
I
t
l
to
t
Pmria City/Cour*y L*nndflll
Monitarirg Poir lrrfonnadon
Amrnl Repon l9{9
.YAI\IIDE,
&n-,-- "^
Pqlrt. *!s4|*s
{ *,-^.*
!*
Ft**r* {kwp**p*. *i
T
l"
l;
t9
h
*l
r:[-*-*l il
CYANIDH, TOTAL
G03S
)3S
G04$
G05$
G02S
I,"l i l"{
",E;;l ,I**l
il
t
I
I
I
I
I
t
I
t
t
I
ft
s;g*
Gl1$
T
I
II
I
""1
tl
-L-J
l
!44&lAnlatlr
ci?s
-T****l
t
I
I
I
t
lr
G06S
""1
tl
l
I
I
I
r"{
",1
I
E
I
I
T
I
rl
"*l
oolJd44.d
efrs
G24S
tl
"T1
",1
haAu&*rfrrdtt
J
I
eils
effis
0Brnffil
Elt
"4
ftar!)at*rn
"J---,;@.J
!a4btrttrrt.
E..l
tt
cils
"r**l
"tt
tl
.l
t aurII
t
3
T
1
tt
lt
I
I
.l*-*ffi],
g
I*
i
n'su,,Ts Fo* c:ANroE, rorA..
ftrr*r*
r Case ID *
DATE$
rl?s
:.GF*
G€-q
It+o
GQgS
I l{ininum
o, *r*u"
-!Isxinum
Illean
-
qESUI,T
0. 009
0. 009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
LNCONCENI
-5.404 ng/L
*5.404 nq/l
UNITS$
-5.404 mg/l
-5.4$4 nq/I
-5, {04 mg/l
*5.404 mg/l
-5. d04 mg,/I
-5.404 mEll
-5.404 nq,/I
TNCOIICENT
-5.404
0.004
-5 . 404
0. 004
-5.404
0.0
Dev
GRTIESS
CO!{POUND$
22.000 C:/anide, Tor
23"000 Cyanide, Tot
24.000 Cyarride, Tot
25.000 Cyanj.de, Tot
26,000 Cyan:"de, Tot
27,000 cyanide, Tot
28.000 Cyanj.de, T.r
29.000 Cyen.ide, tot"
30.000 Cyanide, Toc
CONCSNTLqTIO
I
Gtandard
QTR
961021
970i.13
9?0505
9?0?14
9?10?{
9801??
96040?
980805
981112
G0eS
a-
0.0
3EEsa55F*-=
l* Ca6e ID *
I03$
Io:s
G03S
G03S
I03s
I03$
E03$
G03S
QTR
DATE$
981. L
COMPOUND$
22.804 Cyani.de. Tot
96r.021
9?0505
9?0?14
9?1.02{
980:.14
98C407
980805
24,000 Cyanide, fot
25.000 Cyanide, Tot
26.C00 Cyanide, Tot
2?.000 Cyanide, ?oi
28.000 Cyanide. Tot
29.000 Cyanide, Tct
30.000 Cyanide, Tot
12
bKI![J)
RESULT
<
<
0.009
<
<
<
<
<
<
0.009
0.009
0. 009
0. 009
0.0c9
0. 009
0.009
UNlT5$
LNCONCENT
-5. 404 mgll
-5.4Q4 nqlL
-5,404
-5.40{
-3. 404
-3.404
-5, 404
-5.404
rnE,rl
:ng/I
ng.'J
*gfL
ng,rl
rnqlL
COT{CNNTRATIO I,NCOIECENI
$,*r*"."
Haximum
$illo.,o
o-"
B
x
0. 004
0. 004
0"004
-5.404
*5.404
-5.404
0.0
0.0
n,:-p
DATE$
ff-.'o.
G04S
Ilil
!l of cases
llin:mun
anMDnrrNnq
Cyanide,
Cyanide,
Cyanide,
Cyanide,
Cyanide,
Cyanide,
9B0B 2 1
22.000
24.000
25.000
25"000
28.000
29.000
>OLLLl
30.00Cr cyanr.de,
961 0Z 1
9?0505
9?:.024
98040?
CONCENTRA?IO
Tot
pFen? f
.049
0.009
a
0. 009
0.009
n
nno
0.009
0.009
<
<
LNCCNCENT
-5.404 ngll
-5 " 404 *gll
-5.404 ngll
UNITSS
-5.404 $g/L
-5. {04 ng,r1
*5.404 mg/i
-5.404 ng/l
7
*5.4r)4
-5 .444
-5 . 404
0.004
0. 004
0. 004
Mean
tot
GRTIESS
LT,ICOIfCENT
7
Haxihrull
Tot <
Tot <
Tot <
Tot <
Tot <
il;;";rl,l-*",,,,;1"=--=-,,,"===.,*il,,'--Tffi;;-----T;il;=-_=ffiffi;*==--=;il;**
Tot
Tot
Tot
?ot
27.404 Cyanj.de, Tct
28.000 Cyanide, ?ot
29.C00 Cyanide, Tot
30.000 Cyanide, Tot
2:,000 Cyanide,
24.400 Cyanide,
25.000 Cyanide,
26"000 Cysnide,
9610?1
970 505
970?
i
4
9"t1024
9S0l 22
9g 04 0?
9808 05
qRlll2
ccucf,I'rTRA?Ic,
r;T;; e ID r
d!!f
&06$
COM?O{JNDS
fot
?2.000 Cyanlde.
9"t0'tt4
25.000 Cyanide, Tot
980 I 04
il3:i
QTR
DA?E$
961.021
97 *1,L3
9S0L14
980406
981 110
<
<
<
<
0.009
n nt,lq
0.009
<
0.009
0.00a
nno
0. 009
<
*5.404 mgl1
-5.404 ngr'l
*5.404 mE/i
-5. {C4 ng,/1
-5.404 rogl1
-5,404 ng/l
-5.444 ng/1
-{ .
-ini
-.
-4tt
+
I
0. 004
0. 004
971" 0? 1
n
-5.404
-5.404
*5.404
0.0
0.004
giandard $ev
<
LNCONCnN?
U
l$,,**"""
0.009
<
a1
nAn
4,,--;t^
Lyarrrus,
!sL
26.000 Cyanide, Tcit
2?.000 Cyanide, Tot
28.0Q4 Cyanide, Tot
29"0t)0 Cyanide, ?at
30.000 Cyanide, Tot
GRTLSS$
RESIJLT
0"009
t.aag
0.009
n nnc
0.0s9
0.009
0.009
0.009
LNCONCENT
-5.4C4 mE/l
*5.404 rng/l
-5.404 mg/1
-5. 404 mqll
-5.404 mg/1
-5 " 404 ngll
-5 ' 404 n9,11
-5. 404 ng/i
UI.IITS$
I
r
l{ of, cases
tltininun
-_-_-'--'rrMeximnm
I*ean
Feandard Dev
CoNCENTRATIO
I
0.00d
0.004
0.004
0.0
-;n
=u-*-:=
rD *
DATE$
1l:-ase
^-- _^
961022
I07S
T:!
??0113
G0?S
9?0506
jll:
:l?:i*
;, rvcl
I:1:o
D?S
S80114
lE*:s
990406
G0?5
980821
981.!"10
diCI?S
I
CONCEII|TRATIO
I"-N or_ cases
9
!6!ninum
0.004
0.004
$aximum
0.004
I!{ean
*Standard 0e'r
0.0
I:*********
r* Lase iD r
oATa$
ICSS
961A22
ES8S
9?0506
GSAS
97071"4
97i021.
f08S
g8at22
Ices
980403
l0SS
COI';CENTF,ATIO
TNCONC$NT
-5.
I
404
*5,404
-5 . 404
0.0
QTR cot4louNo$
Cyanide, Tot <
cyanide, rot <
Cyanide. lot <
cyanide, ?or <
?6, 0C0 Cyanlde, Tot <
27.000 Cyanide, Tot <
28.00C cyanide, Tor <
29.000 Cyanide, Tsr <
30.000 Cyanide. rot <
22.000
23.000
24.000
25.000
cRTLEs$
REsuLT LNcoNcn$? uptrsg
_5.40{ ng/l
0.009
_5.404 mg,r1
0.009
_5.404 mg/1
0.009
_5.40{ *srl
0.00e
*S. 404 n;/f
0.009
_5.404 mg/j.
0.009
*5.404 mg,/r
0.009
0.009
-t"404 mgll
*5.404 m6li
C.009
LNCOIiC8NT
9
*5. {04
-5.404
-5. {04
0.0
QTR coMPouND$ GRTLEs$
<
<
A6. C00 Cyanide" Tor <
2?.00c cyanicte, ?or
28.000 Cyanide, Tor <
22.000 Cyanide, ?or
24.000 Cyar.ide, tor
25.000 Cyanide, Tor
REsuLT LNcoNcnNT
_S .404 rng/l
0. CCg
0.030
-3. 50T rnE/i
0.009
-5.q04 mq/I
*5 .404 &;lr
0.009
_4 . ?1 1 ng/1
c.009
0.009
-S. 404 m{r/l
ulr:Ts$
RESUT? TNCONCE}IT
_5.40{ mElL
0.009
uNrT$$
L}ICCNCNNT
o
c.0c4
l*:ri#"."
Mean
-Standard
0. 030
0. 010
Dev
F*=*?{ase ID r
G10S
frigi
f10S
Q]"9:
G10S
G105
-
0.010
DATE$
951111
?19?96
97IA24
1991?3
9S0123
9e0621
0.004
0.001
Mar(imum
Mci n
0. 0ii4
Standard $ev
0.00c
5
06
91 A1
t4
?70
61 15
97 1024
G}l s
980115
940403
990404
981109
-s. szl ms,/l
_5.404 n;/1
-5.404,n;/1
,se ID i
OATE$
361422
970506
914"1 14
971024
9801r"5
980406
980804
981
1
11
0.009
0.009
<
0. 009
Cyanide, Tct
Cyanide, Tot
0.009
0.009
0.009
0.0c9
Cydnicie, Tot
Cyanide, ?ot
vfe..*sv,
0.0
Dev
Aa1
?n nnn 1'rr:n i rlo
0.004
il"004
0.004
Mean
til;
*s/l
ftglt
0.048
26,000
21,044
28.000
29.000
I
l$:;i**i".'
Gl 2S
0.00e
0.009
0.00e
0. *09
0.009
_5.404
_5.404
-5 " 404
-a
24.0O4 Cyan:"de, Tot
?5.000 Cyanide, Tot
CONCSNTT{ATT€}
*?r
eTR Coi,tpout{D$ 6R?LES$
<
<
26.00C Cyanide, Tor <
2?.000 cyanide, rot <
27 .O{}B Cyanide, Tor <
29.000 Cyanj.de, Tot <
ZZ,}?A Cyanide, Tot
24.000 cyanide, ror.
22.00A Cyanide, Tot
96rC22
$tandard
0. ?70
b
Minilttr:m
tiit
-4.9'72
CONCEN?RATlO L}iCO}'CENT
F of *ases
Iii;
-5.404
T^F
0. c09
.uL
-5.404 mg.zl
-5.404 mg/L
-5.404 ng,rl
-5.40{ ng/L
-5.404 mg/l
-5.404 mg,/J.
*5. {04 rng/l
-:r.quq mg,/.1
LNCONCENT
8
-5.404
*5 " 404
-5.404
0.0
QTR
22.000
24,000
25.000
26,000
COMPOUNDS
Cyanide, Tot
Cyanide, Tot
Cyanilie, Tot
Cyanj.de, Tot
2? .000 C)"anide, Tot
28.AQA Cyanlde, Tot
29.000 Cyanide, Tot
30.000 Cyanide, Tot
GRTLES$
RtrSUL?
0"
ilt9
0.009
0.009
0.009
n
nno
0.00E
0.009
c.009
INCONCENT
-5.404
-5.404
-5.404
-5.404
-5.404
*5.404
*5.404
mgl1
xnslr
ng/
L
ng/l
mg,/1
mE/l
mEi
I
*5 404 ng,/L
"
U}II?SS
* qf
ts
sases
CQ}I{ENTRA3]C
I
0. c0{
0.00,1
0. 004
0.0
6*sF IP i
$Afg$
35
9T*?1{
Llrcs{es$t
I
-5.404
*5.404
-5.404
s.0
Q?R
GRtl,gsg
COI'|FOUNF$
aS.0S0 Cyan{de,
?et
<
RdSUIT
0.009
Ll{coNcE}ir
uill?s$
LNCOI{CENT
-5,d04 nq/I
UNITS$
-5.404 urg/l
,,TTEN3RP.TIO L}ICONCENT
11.
0.00{
0.004
0.0s4
*Ii#.ldean
andexd Sev
t
Case
sx{B
t
IS *
sAr$$
9?0?I{
lffiii::. *"
ryE-*-*E-dE€a
I* Cns* IS *
Ir$$
fl.r$s
G:5$
*:"$$
li5$
IXSS
t}$s
s:.is
-5.404
-5.
Riisutf
0. 009
dod
g&s&e*eEs*€g5$*a
QlR
6F*sqa*p*€asss$&e4*s&Ee€EF**eed*s
cOMpoUNp$
22.000 CyaniCe. Tot
2s.000 Cyanicie, Tot
?5.otl0 Cyanide,
26.000 Cyanide,
2?.OCC Jyanicie,
28.000 Cyanide,
29.000 Cyanide,
30.000 Cyanide,
9?:.s30
e8o1?3
9s0406
9808?1
98111. L
Tot
Tot
Toi
Tot
Tot
Tot
GR?LES$
<
<
<
RES{]L? LNCCNCEN?
*5. {04 ng/r
0.009
*5.404 mgll
0"009
0. 009
<
0.009
<
<
0. 009
<
<
0.009
0.009
0.009
U}.IITSS
-5.{04 mg/l
"5" {04 msll
*5.404 ng,/l
-5.404 mg,/l
-5.404 ng/l
-5 " 404 mg/l
c0lrcE$tRArlo tllcoNcEli?
*
88
0.004
0.004
0. 00{
0,0
DAre$
" ".uotu$
lglll?
9?050S
nl$
,,",
fi*
gg3:l
:llti!
ll91?3
-36$
l*ges
f|::
I'ibs
R1l$$
9?0?1d
:::30t
980804
3811:"1.
C0lrcBfitRAllo
I
[N of cases
IMinlmun
$d*xiraum
_ l{oen
I
0"00d
0.094
0. 0S4
{:::::::.:::_=
*
*
_Sll$
0. c04
0. 004
161111
91050?
9?0?14
ffi:::::*******
l}]s
Eln
*jlL
-5.40,1
n!.?5$
$.aximum
.r6l?s
f}lf
I;I7S
Srls
GRTIES$
fot
I.NCOhICEN?
0. 00{
EE5-arym*sx**e*s6*esset
il|k*
case rD
COMFOI}NNS
I
ftinimum
*rgase
* gase r$
QtR
f5"00S Cyanid.e.
ES$CENIFA1IS
o, *r***
-5.404
*5.4C{
*5.404
0.
0
ofR
coMPouND$ cRTLns$
cRTLns$ Rrsutr
REsutr r,Ncolfcn$t
:,Ncolfcn$t
0.00e *i.404 ms/r
0.009
-i,40{ ng/l
*Il cyanide,
^
^^
a?.0c0
rot <
34.0i)0 cyanidg, Tot <
?5 " cuo cysnide, ter <
ci,anioe, rrt
lI.lgg
??.000 cyanide. rot <
?*.000 cyanide, ?or <
29.000 Cyanide, Tor {
<
30.000 Cyanide,
for <
0.009
_5.404
0.009
0.009
*5. q04 m;/1
uN:
uN:ts$
ilrg,/1
*s.404 ms/l
0.00e
_;:;;; ffiii
0.00e *5.
0. 00e
40d nrs/1
-5.404 rns/l
LNCQNCENT
I
*5"404
*S. q0 jl
*5.404
=_"____l_l__-______l_l____
DAla$
961112
::1108
9?0714
9?102t)
980123
980{02
::l?!*
eP:rll
.rd5
fHe 0r cases
^---^
lm
ulninum
I'- ffaa.Uau&
Itls&$
$tarr{f,fd &e?
-5.40{
-5. 404
-5. 404
{OfiCANtR.AtIO
I
0.00{
0.004
0.004
0. fl
QTR col'lPouND$ GRTLEs$ n&sutr LNcoNcaNr
<
_5.404 mg/t
0.009
(
rs.404 ,16/l
0.009
<
_5"404 n;il
0.009
t6, G00 Ctanidei Tor <
*3 . rio{ nE/}
0 . 009
2?.000 Cyanide,
<
22.000 cyanide, lot
?d.000 cyanide. ?or
25.00S Cyanide, Tot
Tot
cyanide, Tor
2e.000 cyarxide, rot
30.C00 cyanide. ror
2$ " 000
(
<
<
0.009
009
0.00e
0.009
0"
i$rrrs$
_q dn, bAlI
-;
:
;;; ffiii
*5 404 mslr
"
*S.q0d m;/r
LNCONCf,NT
I
-5.404
-5.404
-5.4Cr4
0.0
se*a*seqasssss*66e*essBee*ess€€€F
e€E€*ssscEe
t
DATC$
96i11?
9?0508
9?0?14
9710?0
9S0?S3
980402
980804
9gflll
{-a $EIilt
8S
9t 3S
ss
8S
d5
OIR
29"000 cyanide,
0.009
TNCOI']CANT
UNITS$
-5.4S4
*5. {04
.-5.404
c.0
-rcgttualu
i
Ca$e ID
oa
G:3S
sli
Q?R
NATE$
0.009
Tot
Tot
980i03
?ot
0.009
0.009
0.009
t,$ 1
l:-:,.._..
t5.000 cyanide,
26.C00 Cyanide.
?1.000 Cyanide,
28.000 cyanid€,
29.000 Cyanide.
1 1.1
Tot
Tot
30.000 Cyarride, Tot
CONCSN?KATIO
INCONCENT
0.0
QtR
DATE$
?(
ee0203
980402
98S806
981113
C0NCnNTRATI0
I
0.004
0.004
0.004
0.0
r3
9804f 1
98080:
981 r 13
CO$CENTILqTIO
I
0. 00c
0.0c4
0.004
o-"
* ca$€ rD n
friii
0.0
Tot
Tot
Tot
4
9"ttazL
981
CO}iCENT8,}.TIO
0
"
a8
004
0.009
0.009
c.009
-5.4C4 ngll.
-5,404 mgll
-5.404 tngll
nna
nna
0.009
uNiTs9
.-5.404 ng/J.
-5.404 ngll
-5 404 ng/I
-5.4S4 ng/l
8
-5.404
-5 . {04
*5.404
0.0
GRT'LNS$
RESUTT
0"009
0.009
0.009
0.009
Tot
Tot
Tot
Tot
0.00!
0.009
0.009
0.009
ToE
Tot
I,NCONCENT
UNITS$
LI'ICONCb:Ni
UNITS$
-5.404 aigll
-5.404 rngll
-5.404 ng/}
-5 " 404 mg/l
-5. {04 mgll
-5.404 mg/1
-5.404 mglJ"
-5..{04 mg/l
LNCONCAN?
-5.404
-5.404
-5.40{
0.c
COMPOUND$
29. 00c Cyanide, Tor,
30. 0c0 Cyanide, T0t
i10
-5.404 ingli
n
n
Tot
LNCONCgNT
0.009
LNCONCINT
flTp
9?011
RS$ULT
c.009
?ot
22.000 Cyanide, Tot
24.000 e ,rrn i Aa Tî
,q nnn ar'56id6
'l^f
26. 000 Cyanide, Tot
IUL
LVdlrI\ftr
27.000 4,.--il^
2B " 000 Cyanide, Tot
06111?
91050?
980123
980403
980804
| il'::-:i".'
26.0C0 Cyanide,
27.000 Cyanide,
28.C00 Cyanide,
29.000 Cyallide,
30,000 Cyanide,
25.0fl0 Cyanide,
26,000 Cyanide,
2?.000 Cyanide,
28.000 Cyanide,
29.000 Cyanide,
30.000 Cyanide,
980-t{)l
!,taximwE
T^r
24.000 Cyanide, Tot
9?0508
9?0714
97 1 0?0
!$,:i,:fi"'.
nnn arrrnirla
I]TD
E'IMDNTINNq
ruL
za.uvv
Lydiltqer
ufrt$P
9611
€RTJ,E$$
22 .
9? 10? 0
Ytl *
CQMpOUllD$
00tl Cyairide, Tot
24.00S Cyanlde, Tot
96:"113
9?0509
970714
rt
IJ4IJ
0.009
0.009
nq/l
-5.404 ragll
-5.404 vrg/1
-5.404 mg,/I
*5.40C rrgli
*5. {04
-5.604
0. 004
0. c04
-M
-t c?fis
I
IN af ca$es
l{ini&um
}larimum
l$ean
IStandard Dev
*iii
0. 009
-5 " 404
s
lit::ix",*"
15
0. 009
*5.404 mg/l
- 5.404 mg/l
-5.404 rnE/l
*:.404
0.004
$ini^&lxr
I'lllt
Gt)1F
5.^
^
LtC *b
CPTT trqq
2?.000 cyanide, Tot
24.000 Cyanide, Tot
980804
f* Case ID r
E30$
*ras
G?gs
_-G?OS
lf
COMPOUND$
96:.11?
97050$
9?0?1.{
9710?0
9S0{02
sx9s
f
0. 009
d nno
lot
UN
*5.404 ng/t
-5. d04 mglI
- 5.4t)4 *q/L
*5.404 mg/}
-5.404 mg/I
*5.404 mg/l
*5.404 ng/l
-5.404 mg/I
LbICONCTNT
L€v
flilo",o
0,009
0.009
0.009
ITS9
TNCONCENT
o
ltlaximuiq
G2
0.0c9
30.000 Cyanide, T0:
0.004
0.004
0.004
Hinimurg
f .1o
DFCITT T
0.009
2?.C0. cyanide, Tot
?S.00t Cyanide, Tot
COSICENTRATIO
*
GRITES$
?6.C00 C'anide, Tot
N of, ca$e$
-teqn
COHPOUND$
?2.000 Cyanide, Tot
:4.000 Cyanide, Tol
?5.000 Cyani,de, Toi
LNCONCENT
-5.404
GRTLES$
RSSI]LT
0.009
0.009
0.009
0.009
0
.009
0. c09
0.003
0.009
-5.404 mgll
*5.404 mg/I
-5.404 ngll
-5.404 mg/l
*5.404 ng/l
-5.404 nq,rl
-5 " 404 ng/1
-5.4C.{ mg/l
l::1"*
Standar d
0.004
c.004
0.0
Dev
ID T
OtR
e
9?1021
98012?
G23 s
980406
s23 e
980804
000 Cyan.ide, Tot
30.000 Cyanicie, Tot
CONCSNTRATIO
f,-m-;;-:
c24s
,G?4$
124s
Ie48
E?{s
c24s
f?4s
I N of cases
Mirrimum
ft{axi:nu:n
rll1ean
tstandard
t
I
t
I
I
T
T
t
Dev
0. 004
0.0
DATE$
961114
97C507
9?0?14
9?1021
9gul22
9804C3
9S0804
9811.f0
CC$CENTRATIO
6U
0.004
0.004
0.004
0.0
I,NCONCSNT
-5.404 rrg/l
UNITS$
-5 " 404 mgll
-b. 40{ $,t/1
*5.404
*5.40{
-5. 404
*3.404
-5. 404
tnE/l
mg/1
mgll
mqll
nqll
LNCONCENT
R
0.004
RNSULT
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0,009
29 .
0. 004
$il*:.,."
GRTLESS
24.000 Cyanide, Tot
2$.000 Cyarrlde, Tot
26.000 Cyanid€, Tot
2?.000 Cyanid€, fot
28.000 Cyanide, Tot
98i1i0
N of cases
cor{POuND$
?2.000 Cyanide. Tot
97 0? 1.4
r
nn
DASE$
113
91050?
9 61
c
-5.404
-5. {04
6
*5.40d
-5.404
-5.404
QTR
22.000
24.000
23.000
26.0C0
2?.000
28,000
29.000
30,000
LI-ICONCSNT
-5.
404
*5 .404
'5 .404
0.0
CO},IFOUIiD$
Cyanide,
Cyanide,
Cyanide,
Cyanide,
Cyanide/
Cyantde,
Cyanide,
Cyanide,
Tot
Tot
Tot
Tot
?ot
Tot
Tot
Tot
GRTLBS$
Rf,SUI,T
0.009
0. 009
0. c09
0.009
0"009
0. 009
0. 009
0.0c9
LT,ICONCENT
-5. 404 ng,rl
"5.404
-5.404
*5.404
-5.404
-9. 404
ngi'l
rngll
mg,t1
nE/l
ng/l
*5. C04 mg/l
-5.4O4 nqlL
{J};I?S$
I
U[,]iIDE, TOtAt,
REGRASSIOI{ VAI-USS
?&t t10)t-ssTEqT, aacRns$xoN NoT
la
Fi-
,-iv
I
I
T
T
t
t
n
il
t
r
il
I
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T
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il
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,
tt
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I
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t
I
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t
I
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-
$
300000
270000
Affi*ffi
*
240000
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F
(t) 21 000s
:)
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1
80000
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1
50000
1
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1990
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t
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1.676
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??,00S Xr*n. Si**cl.
sAlS$
9610?1
:I
9?0505
lrsn, *is$sl
lr0n, Pj"sd*X
t?.000 Irsn, $is**1
2S.000 Irsn, g{,ss*}
?9,000 lro*, 0i*sq1
e6,000
9?1024
-,{;}
Eoas
9801"2?
c0e$
900s05
J"gf
N
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sls&, *s#
ss
?S"000
9?0?1.4
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&s$r3L?
F54*, S**
845* " **S
73.000 Xron. Sissnl
?{"000 lron, Sisse}
9?0t 13
-E*
sfiTLS$S
98840?
30.000 1rsn,
9811 I ?
CONCEbIfRA?TO
cases
s3*s _ *s*
s9**. s*n
*S** . SS*
I
t?*s*" *e*
q4.*fi ilhft
nis3,*1"
L$*frS#SeY
9" 1di3 *611
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$"S43 *ry/t
S.19# ugJl
l3? *q13.
S.#?{ uql}'
S.
15S ury/tr
S"
3iS *6,i I
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3"
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t HcoNcsmt
:t
5500. 000
*i$::.,."
I ?000 . 0s0
9143.333
9"393
1?3{.905
a,2L2
9. 102
*e*se*€sesss*s*&e&asesqS&*&a4**&4:&S**&&e*ee44g$s
Qr8. C0HrS{,tX,1pS
?1,000 lron, Piss*l
?4,000 lron, Dievol
25"ilSS lrslr, Sis$*I
?6,000 lron, lliex*l
27 "fiQg !rr:n, Oiseo}
?8.000 Ir*n. D1*s*l
29.S0$ trron, 0is**i
3S,000 Iron, Si*ool
DA?f,S
?e
961021
9?0505
s$3s
970?t{
97 I
*:i
0?4
98011{
98040?
G03S
9B 08
05
981112
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CO}ICENTR.n.?IO
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6S?LS5S
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t?00. 000
5400.0s0
267L.259
7.A90
1355.949
0.483
3$*S " S**
? " ffJd
6pl.l"
3
S
l;6,11
l0*. &s*
"
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u.
7
f:r{l
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lil*:n.
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?2.S#S Ir*n, *issol7r' ilfi/l rr"nn
ni an^!
s6LgzL
9?05 05
q?0?ld
97ltt24
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9S 08?
I
981.112
co$cE$tRtTIo
7
*,li*ii-'"
6000 . 000
1
22&$0.00t)
I{a:cimum
L'l6*5.7t4
ilean
2955 .47.3
r::::::":::
6 Cas€ ID
*
tir
sfls$
f;ir
9?t*24
984127
98 040?
98 0$ 05
98ILL?
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1
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"
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33**# " *S*
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26S0.000
7.601
7.863
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26"0{]S Irsn, Siss*i.
2?,0S0 lr6n, $isspl
28 " 00i3 Ir0r1, Pisso:
??"eS{) lrsn, *i"seol
3e"*ao :€snr si$s*l
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96L421
9'79505
tli*ff".'
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z3.vuu tron, ul.3$ot
26.09{} Irpn, Di*s*L
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7.9.40* Iran, $i*sr:l
30,000 lron, Elss*l
980{0?
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?. *P{J *S,r:
L!,rgoNcelrS
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96182X
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9?$? I
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23.8** Ir*,x, tlie$o}
?$,Sfi# Ic&x, S$ss*l
2$,0$* If*lr, Si&s*i
2?"SS0 lrs$, *i$*sl
980486
S3fl{
?8"00S Is*no Slps*I
9S
17. uul,J I ron,
98I11$
30"SCfi
[Jtg501
1r*&, **sssl
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$
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36*fi " *0*
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6.4*-; x1qli
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"
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,+61
i
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I
COI.ICENTRATIO LIICONCSNT
I
I
of, cases
t{
tol ? 'tRn
6.80?
8.45?
?.883
1159. ]00
0. 5:.0
900.000
nimum
ximum
.1?10.000
&@s**&*ds9*@&&s#&s*
Q?R C0!{?o{n:ns
22"000 1ron, 0ieg0
?3.000 lron, Dig$*I
?4.000 Iron. DiE$*l
25.000 Iron, $i$s6l
?6.000 lron, Oissol
??,0S0 1ron, 0!ss$l
?8 .0{10 lron, 0iasol
29.000 Iron, Pis$*l
30.000 :ron, $is$01
96t022
9?01t 3
9?0506
GOTS
9?0?14
9?1021
frit
980r]"4
9e0495
G0?s
9S0S2 1
98 1110
ffr*
SONCSNTRNTTO
of caneg
d{ininun
N
Ii,taxlmum
Standard
-raFe{
[-m-r:
I
210.000
4000.000
2173.333
5.34?
8.294
1309. 399
0.927
I ?S*
1
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CONCfiilTRATIO
*5* " ***
d*u* " **{i
33*,&
11fl0.000
r600.000
1400.000
l-89.73?
Mean
:::
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FF4EBaBEg
*
dAA
lrnn
***
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30.00S I{sn, &ir}ssi
9?103r
dtq
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A{. S0A lrsnr fii.sne.},
A&. {}0S 3r*ne S$ss,*&
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at
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W k?S ,a$l i,
"
#.
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g*ffie$.$$w
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ator neu
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ffi
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t{ulti.ple ftl
Trfr qff{C&t{f,RAflo ilr t
S.tr?}
#qua.r#d
ffix}*tpl*
&.; S"&}&
ffi
p
irtsd squar*d $ulti$}s frr 0,$ star.dard slrar sf &etfnsets; l*3*"T63
foef{l*{cnt
t1?3? " 66?
*80.X61
ilffi-
Srrpr
6?$$. ?S3
?3?,lil$
$*d
$un*of**qunr$p
349S01. $$?
2.36p3Sfl*0?
tr116l:
!f**
A14$1116
***
Purbin*lfateo& D
Order
0f
I
7
I iE an outli*r
S ls an outller
r*
lfst
*e#f 9*}*x*nst
S
-*.X,?t
*.
t
F{S ?astl
$tatigtie
!{ssn*S{iluffxs
f*&t*.ts
3*$S$3. gS?
s, gt4
S.
1
l
$
*,?'*S
s
n '!6C
13S4?99,TSx
{&tlrd,*n?tpsd &*etd{}e}
ry
{3*ud#n*ised &***d*sl o
3
&Srl
*4.' SSS}
2.1?$
Autocorrelation -0.120
ror:
*"$;}l""tnn "l'ilirare
g }4ltltip}e ftl 0"1$} Squared s&ti.tits}s &r S,S}&
lp varr coilcsl{TRArrs t{r
ljuua*a lguared Eultisls &; 0.s *ta&dfird *rrcx *f, &6q*!Bs*e; i{$s'?},*
q tr{tr f&sA}
. .&tr&
0,0
q.t03 1.000 *"x$?
0.?51 :.s}fl
$td gsrsr
fsnf,fiqi*nt
1t93.S0S $d$4,$FS
Sffeat
'
44,
$td e$ef ?stros*:rery
{uo..ev
..-3l)
sf Varj"alr**
$r,.rc-of,-$quarer $f Xsen*$Ex!8{6
A&alge{g
t*.-
1
6
136191 . ?S*
R+Er*n*j"*rn
L,2't32l.**#7
-
T:::::__-__
itr fiAIWING r**
CapG
13
i* an eutlrsr
f*&et9*
1361$1. ?S*
$,
*s*
u.6urt
?1t301S"S{*
i qirviont
e
rad
Q4e! f,llla i
*
t
?4': l
***''r:*:%l.l:**i:ri* i.f{l
fsllorlsg rsslilts ar*
* 005S
t*gtl.S
f,orl
lt8r! g${ggiltftATl0 !{; S ilult:ipl* Sr 0.SST $qtlsEe'd 4s&*ltip}s &r *"?1&
sgqared nuttiplc &: 0.0$S $fa;rdasd erxEr qf sstl&#'fist
fiusted
'?S";*SS
Sr-d Cii€f Toierancc
t f ii
$Ltl Error
Cc,ef f iciene
*ect
3190.226
-37.33r
*,s
{i6r .584
?4.9'12
-*
"
46?
sf v&ri&$s#
$uF-sf-Sguar*e Sf l{e6$*$ry$ess
s?l33.dCS
I
$2133 " 45S
.
d"*gfr
1.$"S0 *I.fi$S
&"e*3
*"*e&
AJralysi$
1S66X6 " $41
fl.&RNlNG
gagg
4
?1
ln) lq?
F*&s.*{s
3"S?$
s-343
t**
3? i.e a$
slltli8r
?3 Ls at\ sr}tlier
}.:txa::.N,f":;r:;il1f,,,
-fr:?ifr
{
{
Str*d*r3c{ ssd &*E*di**}
Stlrder:t *aed &ss;*"Sua}
ffi
@
**$
"
*S,$3S
I.SSS
1,
Analysts 0{ vflrt{twe
t**
Ise
S*d
ire
ft.k{xv}
"'fr"3Ttr1
d
$s
hw
f,ollorlnE results arc for:
.
Varr
cdis
CONCENTRATTO
*qqe,r*d
#w
G06$
N: I
&ultipls
Rr
Uul.tiFls R,l
0,484
Coeffleient
Sgd
0,?{?
,$tandard
Error
-30?,342
*rror sf *stlnstlt
f.0
-0. ?il?
1Xl.?E8
w
ffi
83S"d?6
t
Std Co€f Tolerance
2949. {33
xc96x " 4fl6
W
gqultsd *uXti$l* Ar $"$*?
r{2
3e1}}
.
3.??$ S,*tS
x.0*s *?.?{9 *,03}
Rgsreesion
I
5212492.805
{162095.495
$*::l-i*r gA'{NING r+*
nf
x
6
31 is an outlier
f"
2.301
D Statictic
$bin-$atson
Firrt order Autocof,relai.ion -0.20?
*:tl;uar*
,
ff-*ii**t"*
?ar:
*ONCnNTAAI:0
Sel'
tiff-
&'6
}tufl$*squar*
P*net*f
5t{2492,0S5
?, $$?
.#e
;&t
ffi
0. *33
6936S2.383
(Studentiaed Rosidual
*
-2.971
)
f,er:
9
"*"'.:#::::::.-'
S:1T.
ii
!f:
Fllrltiple Rr 9.1.04 Sq*arsd :qultiple sl 0,811
0-0 $tandard error qf, s$t*ealer 139?,18?
$id geef, Tqleranee
Std Errot
3{69,000
4695,964
'e9,833
1?$, ?30
0. 0
*0.ls{
t
P{?
9*i}}
739
I
0.
"00c *0.9??
0. ds1t
s"?9s
An&Lysis of, variance
-.
$um-of,*$guares bf Hsan-S$rsre
ilffi*
149001.6S?
1.3S6?2s+0?
t
?
f*Ra{is
t
0. ?*s
0"0??
1*9S01,6$?
193*1?1. XgS
t.,::;.,"": ;,,".;:"
t.&22
Frb*n*ra*son I stfltlEtlc
first ord€r Autocoffelat.ion 0,155
*"fill'"t'n
"lullirare
ror:
Util|iple &l 0.3{? $quarad aultrple ttl 0,1?f
lJueted sguared nultiple R; 0.0 $tandard *rrps af, estieaiel 2*96,343
trl
Coefficlent $td Error Std efi'ef Tolerance t 9i* ?E$3)
pop
t
Var:
CONCSNTRATIO
N: I
T.
9589"?66
1{308.?96
*32't ,945
351 , 9?d
ru;;;
r&rg{Eoalon
silm-0f-rrquares 9F'
Mean*$qs*r€
I
6
$3639dr. *St
*363,948 "L5A
3.92'tq3g+0?
*AP,NII{G Tt*
Cege
i
,
0S0
l,dg?
. $CI6
-0
S,16S
$.
{ss
Arialyais pf Varianc*
li"*
I;':::
0"0
.747
-Q
48 iE an
putlier
f*33*is
CI.
E
$?r
653{8S9.S9}
(Siudentized Residual *
*2,?4*tt
2.424
ng result.s aEe
*
M
trc
:ry{e
&d
Anrl.yllu pf Variansa
Sun-of*$quqr$s
4
feq
fotl
G175
?arl **!{CSFTRAT[9 ]l; I qirltipl* B.r 0.219 squfrred #$]tipl* &r n nio
aguared nuttiple R: 0.0 standard error of eatimaEet 217-205
ffiusteC
std epef ?eler*nse
*
P{? ?se3}
coeffiaient $td $rrqr
ffect
r039. s94
39. e$*
0.0
0,
ttg
0.
1.000
0.
{$5
$$1
0. 665
CI.
sst
Analysio of, Varianee
Sun-of,-Squar€s DF llean*Squars
t
6
2333r.362
461055.13S
58 i.s *n
tso& O
2333?.362
76842.523
outlier
Statistic
p
F*Ratio
0.30{
(Studentized Residual
0. 602
-
?.265l'
1.90?
l{fst Order Autoco*elatign -0.1A6
n:.._fottoHing
-,
resuits are forl
Ie
--_-^
rr EPYYC
*- qr
^t5S
l. """"t
DQp larr
1,.'
Dusted
Sffect
N: 6 l.tu.ltiple R: 0. 111 Squared rnulttpl.* R.l 0. 011
squared nultipie R: 0.0 Standard error of estinater 732.4J3
Coefficient
Std Error
Std Cosf Toleranea
t P{2 tail}
COl{CENtR.etlO
?484, {61
$**'
2'r47.6t't
*2S.3?1
103"711
-0.
L:.1
1.000
0.904
-0.2?3
0,401
0"
?94
Analysis of, Variance
Sus*of-Sguares DF
ffi*,,
t"
40003.
i33
3218746.86?
1
6
is an out]ler
2.1lrJ
Et-flatson D Statistic
:-0rCter
AutaccrrelBtion *0.267
F7
,the
fe}lcning resu]"ls
ar* forr
.rEF?r.
_^.6$
!{ean*Square
F-Rati0
{0001.133
0. 0?5
53645?.811
{Studentizeci Residual *
65
P
4.294
5.757t
a-.
I
lp
*-'
var:
CoNCENTRATTO
&dJirsted aguered
l|.*
{w$tA!{r
N:
B
rnu.Lt1p1e R:
t{ultip}e &: 0"760 Squ4red rnul_tip}e Rr 0.S??
0.50? standard error of estimate; 1.0d6.5:?
Coeffiqient
$td Frror
-s13d.586
3925.942
1{8. t85
Tolerance t F{2 Tail}
*1.308 "239
0.0
0,?50 1.fl00 2.862 00"s?9
$td Coef
QTR
424,06fr
Sqguee
Analysil of Variance
sur-of-Sguores pf Mean-Sqsare
t
ftm:i*
1
6
89688?2.180
651LL?7 ,828
?4 is an outlier
S"t*t**
pu.cbin*Batson D Statistic
89688?2,18S
109518?.9?0
F-Ratio
8.18$
($tudentized Residua.l
-
P
0.029
-2.144)
2.1.00
Order AutocorreLation -A-2i2
Iist
*#ll"-'
var:
r
lusted
p,
nn'"3'ilirare ror:
g lrlultiple R.: 0.594 squared nultiple &r 0.468
sguared nultiple R: 0.379
sg*ared.,multiple
0.3?9 Standard
standard error of estimat€:
estimar€: l35S"ggz
r35s.gB2
Coefficlent Std Error
$td Coef Tol.erance
t P(? raill
C0NCENTRATTO
N:
1?351,353
-443.985
5123.910
I93,407
0"fi
-0.684
1.000
Analysin of Variance
$."
Suo-of-$quares Df'
!!ear|*Sq*Ere
f-*a*io
3.346
-2.296
8,823
0. 06r
*iur
I
**rn.
9831
L
{92.01L
119388+0?
'**
ol-""."r" o ,...r";r.-
9831{9? " 01L
186563?.581
b
--;.r*
5. ??0
(Studenliaed Residual -
0.061
-3.336)
*"
[';;::;",.":::':::":".,'
i
].I
var: coNcENTRAtro N: 0 Multiple R: 0.40? sguared rnui-tiple R: 0.16ti
AdJusted sguared rourtlple R: 0.02? standard errior of estimate: 964.g1.9
C0efficient Std Error
9{05.614 3619. 3?9
*149.123
xn,
L35.61?
'n"*
Tolerance t p{2 fail)
0.s
t.599 0.041.
-0.40? 1 . 000 *L.092 0. 31?
Std Coel
of Varj"ance
Sum-of*Sguares DI. Hean*Square
1109:.00.8?? 1 1109100.8??
5585249. r23
6 9303?4.854
Analy,gis
frfili::
is an outli€r
D Statistic
?-7"13
86
F*Ratio
P
1.191
n
=
?1't
-2 "!451
Fisgt Order Autocorxelation -0,398
ror:
fd;ii""t'n'ul"*lirare
var: goNcElITRAtro N: I Hultiple R: 0.?0G sqriared multiple R: 0.498
sguared nultiple R: 0.414 standard error of estj"mate: 3?90.129
Ied
Bffe*t
Coefficlent Std Srror
Std Coef Tolerance c p{2 Tail}
*8975.190 1{?18.1?9
0.0
If$lAl{r
-0. 631 0. 55i
1309.524 536.676
0. ?06
fr
1. 000
2.440 0. 050
i{,nalysis cf Variairce
Sum-of-Squares DF ltean-square l*-Ratie
IBrCe
f,
8.552838+0? 1 8.552838+0? 5.9S4
0.050
ngFrgudl
9.61905s+0? 6 L. {36518+0?
bep
I:;
E
-AdracaiA6
l
tfAlllllNc r*r
Case
g?
ie an outlier
2,726
]Utrr-tlatson D Statistic
Order Autocorrelation -J.3?4
lrst
The f,qllsr.dng results are for:
(Studentized Resldual'-
* 6205
XEIIL$
?ar: C0$CnNtRATI0
N:
o
Multiple R: 0..9?9
$quared
raultiple R:
AdJurted squared nult:ple
0..172
4.734 Standard error of, estimater
Coefficient
Std Error
p(2 Taill
Std Coef Tolerarrcq t
3645. 9{3
-5577.043
0.0
-1 .530
0. 1?l
ozu. f, 3l
13?.620
0.879 1.000 4.509 0.00c
Analysis of variance
p
Sum-of,-Squares DF l.lean*gquare !'-Ratio
1..9?0618+0? 1 1.920618+07 20 " 333
0. 004
565?534 " 837
6 944589. 1{0
IBat
col{5tAN?
r
itt,'.
i{AKHIFIG
2.55S)
g?1..900
***
102 is an outlier
(Studentized Residual :
*2.500)
#
*=*.rrr,*%?":::::i:ri.* -i. *r
ror:
Jr5lii"-t"t "i"ilirare
ilt
ia
h
-D€Ir:
-V
lustea
N: ff Multiple R: 0.305 $quared multiple R: 0.093
sguared multlple R: 0.0 Standard error of estirnate: ?90.699
CONCENTRATIO
f,a*.a
coefficieqi
std Error
std eoef toLerance t F{2 Tail)
?61. . {04
2966.194
0.0
0.25? 0.806
8?.119
t11.962
0.305 1.000 0.?83 0.463
Analysis of varience
p
Sun*of-Squares DF !{ean-Sgurr€ E-Ratio
383??1.930 t 3t3??1..930
0.614
0.463
3?51??8.0?0 6 6?5?04.6?*
I[rsEA}{T
T
i
Jrce
Gr"ss.or,
R€sisual
nr*Fa-'r--
L,-,.-.r-.,^
I.
r&trlttb
I
___
^--
Case
is an eutlier
D Starisric
1.792
]bin-ltateon
order Autocorrelation -0.002
Irst
I
ror:
109
:.*{ll}*t"s
]-
Varr
ndjrl.sted
**egN$TAt'!?
n
qfir
Soutce
{Studentized Residual
-
-2.650}
"*l"i!iuare
!{: I Hultiple R: 0.06? Sguared multipl.e R: C.004
squared nultiple R: 0.0 Standard er-or of estimate: 1694.950
p{? Taili
Coef.f,lcient Std Error
Std Coef ?olerance t
?765.31! 63s8.36?
S 0
1. 2?l
0.268
"
2{0.002
"39.348
1".000 -0.164 C}"8?5
-0.067
Analysi.s of Variatce
gur,r-of-Squares DF M6an-Square F*p.ttio
p
?7221. 1?8
7-1221.L'r8 0.02?
t
0. 8?5
1. ??3?18+07 6 28?2854,801
CONCENTRATIO
*ruii::
ni !{NINING *.+
l
is an ouglier
D Stati.sti.c
1.,{?8
115
Ise
-br.lrbln-tratson
Pir*t
(St,udarrrizeci Resj"d!'al
=
8.905)
Order Aut,ocorrelation -0.013
follouling results are for:
*
$AI,L$
ry Varr
gf,f,eEt
ft"**
*sg*e*sion
lfgll'$
i
*
N: I
Uultiple R: 0.6?2 Squared nuttiple R: 0.{52
!0u1tip1e R: 0.360 Standard error of estir$ate: ?3S.1-01
CONCcNT&ATIO
Xi?isted eguared
1*,."
c?3$
p{2 Tail)
Coeffj.cient Std Sffor
Std Coef Toterance t
694.160 2?5?.62S
0.0
0.252 0.910
231 .454
t 04 . 089
0. 6?2
1 .000
2.224 0,068
AnaLysis of Variance
p
Sum-of-Squares DF ltean-Square F-Ratio
26?18{2.988 1 26?1842.888 4,944
0.069
*
c245
Varr C*lgCfll?RATIO N: I
Mu}tiple Rr 0.2{4 Squared rnu}tiple R: 0.059
i",
{i!
t
f
i!9
&t
f1"
4e
t{s
tit
Y'
tl
gguired nultipl.e R;
0.0
Btandard
Coef,fieient Std Error
! .61?
-83 ^ ?08
3583.3?7
x35.258
564
effor ef estlnate: 955.!21
Std Coef, toleranee
t F{2 Tail)
0.0
.
I .854 0. i13
-0. ?4{
1.000 -0,615 0.561
of variance
Sun-of-Squares DF !{ean-Square
34531.3 .283
1 345313.283
54?{586. ?1?
6 91?44?. ?S6
Ana.!"ysis
f,
-*;..:
ease
L31
is
an
outlier
$1";la::'1,i.:::::i:i;."
I
t
I
I
I
I
t
t
t
t
t
I
-i:
g*Ratio
0.378
(Studentiaed Residual
lii
=
0-561
-,
oq4l
:,it.i,l
i
lir.,:
DISSqIVA$I RECRSS$IOI{ vAfUES FOR tn Of Cor{gngrnATlo}t
*
I
.A[F
St{
FID ilOT
TltU$, }to 8s6n8$$Iot{ At{Aty$t$ HAs psRronue0
CHANOS,
GOdS, G08S AllD G10S HAD AgSn SAUPL8I) LESS THAN
I
QUARTER$I
IH$S' N0
AE$ffiSSION â,$ALY$I$ $tA$ p$nru&t{*S
rosults are f,or:
{ cczs
Var: l,llCo$CgNT Nt
ilul.tiple R: 0.?3?
9
ted sguared multiple
R:
0.0
Coeff,icient
g - s?s
-0.018
Ifect
]lsrnnr
Qre
Std
Sguared rnulti.ple R,: 0.0$4
Standard erssr sf,
nrror
0.74i
4.0?9
estlnatet 0.?el
foLerance t p{? Xait}
o, o
1? .8{4
o. ooo
*0.?3e
1.000 -0.63$ 0.5d9
Etd Coef
Analysis 0f variance
I
tt"*
Df Ftsan-Squale f-Rfltis
0.019 1
6.019
0. 39?
0.342 ?
0.0d9
Sum-of,-squares
ffi!:iI*r*
ry;{itFllfg
***
llr"
lu*
8 is an outlier
9 is an p$tlier
(Srudentlzed ReelcJual
(studentia€d a'esiduat
*
*
F
s.549
2.395)
-5.252)
$t}rbi-$-Hatson D Statistic
2.040
Order Autocorrelatlon -0.2'16
lrst
l"rflll"'nn'"l"l;i*ate
ror:
t{: S Multiple R: 0,1i13 Sguared eu}tiple &: G"0?S
f3uua"O sguared nultiple Rr 0.0 Sta$dard error of astj.mare: 0.SL?
gtrefficient std Srror
Fffeet
Std Coef tclerance
t ptz fail)
7.105
r.$38
0.0
3.667 C.s10
a "026
0.073
0. 143
1. 000
0.353 0. ?36
gum*of-Sguares D!' I{€an-square
f,*Ratio
E
|'"*
n ??<
0.033 1
Begreeaion
0.033
0. 125
fp Var:
LNCONCENT
F
L OUr
---
b
l::::::--*** f,AllHIbiG ***
13 is an erutlier
Ca.:e
-Irbin-Batson D stati3tic
1.508
frst Order AuEocorrelatlon 0. 1?6
fl",#;i*""'*"*i"l8irare
ror
v, ao
I
(Studenbized Residual :
2.t44',
:
Cn Uur, LNCOIICENT N; I
l'rtrltipte t: 0.4?3 Sguared multiple B.: 0.223
J3u*ted squared nrultipl.e R: 0,094 standald. error of estiruatei 0,0??
gtd eoef ?oJ.erance t p{? ?aill
Coefficie:?t std Errsr
lfect
8. 131
-0.014
0.288
0, 0
-4.4?3
0,011
Analy$is sf Variance
I.;n-of *.9qua:es DF ![ean*Sguare
Egr:rsrANr
-fr
4
f:::" ion
t'
0. c10
0.035
I
nAllhtltlc ***
is *n outlier
3,201
grbln*9fatson D Statistic
flrcier Autocorrelaticn -0. 616
frst
-
23
ilt0
1
0.
6
0.006
?8, t"8s
1.000 -1.314
l-qs'
io
L.i25
{StudenEiueC Regidual
=
0.0$0
4 "?.37
3
0.23.j
-? fii e\
l**
"*:'tll*""*
I
aultlple
Multlple Rl
D,qp,.$arr INCONCEIIT Nr
agusrnd
0.635
nulriple R: 0.403
0.303 Standqrd errsr of estlfiate: 0.125
R:
Coef,ficient
Std
10.89?
-n 11q
EffEr
1.506
0. 057
$quared
Tolerance t F(2 TaiL)
't .23{
0.0
,
0. 000
*0.63$
1 . 000 -?.01.t
0.091
Std Coef
Analysis of Varlance
gwn-of*$quarea DF *lean-Sguare
1",*
degrea$i:on
0"?3?
1 .086
&*aidual
0"?32
1
n
b
F;;;;;-:::
*a$e
31 j.s an outller
f-Ratio
4.044
101
{$tudenti.zed Repidual
-
p
0.09]"
-5
."17
A',t
2.437
frbh-Watson D Statistic
lrst Order Autocorrelation -0.?44
he .f,e}l,sr*ing results are for:
* Go?s
Itr sal,T,s
-.'*-r_..-.'
H:9 Multiple R: 0.141. Sguared nultipte R: 0,020
!*a
Ty
l*J$sted squared m'ttltiple R: 0.0 Standard error of esti$ate: 0.gg1
IrFa^t
.â€f icient
:*--"
std Srror
Std Coef
t. p{Z tail)
2.616 0.035
I . 000 -0.3?6 0. ?:.8
Toleranee
3.308
0_ 0
0. :"??
-g .1.47
Analysls oi Varianee
Siln-of-Squarss DF ltean'Sguar€ F-Ratio
0.136 1
0.136
9,142
6.733 7
0. 962
8.554
*l*srArfr
-0.048
-o
I
-
f
$olrr6e
l;iEs:i.cn
Ftuar
-.---'"
I* Faell .rN/: * * *
IIse
I
39 is an outlier
(StucientizeC Resi.duaI
=
P
U.
'IU
-3.6931
Ourbin*tfal3on 0 Stat.istic
L.696
flrsr- Crder Autocorrelation 0.0q0
foltowi$g results are for:
]e gE
e Gl1S
.$
Var: LNCONCENT !l: I Multiple R: 0,310 $quared reultiple R: 0.096
!p
r.
FJusteO squared muj.tiple Rl 0.0 Starrdard error of estirnate: 0.6F3
I
C*efficient
10.532
*0.0r?
mn-
Std
0rror
2. 563
0"09i
Std Coef
F{2 yaill
ToJerance t
0.0
-0.3L0
4. 110
1.000 *0.?9?
0.006
0.ds6
Analysis of variance
lu'"*
SuBr-of*Square$
0
tilri;!::
***
ldltlll'IING
b
0.461
ts
0.45{
**i
ig an outli"er
2.52A
f$on D $tati$ti*
48
Ordcr Antr)ccrrelaf
'----*-..-,
Pi
,297
4,6U.t
Sf lrean*Squar€ f*ft'atiq
t
0.29?
0. 636
ion -0,
{StudenEized Residual *
"4.6&?)
356
resulte are for:
lFFollowing
e |;12S
E 9IET,T,5
*W tfart [t{COl{CnEf H: I Uultiple R: 0.151 $qirared mu}tip}e &r 0.013
I.
IJusted squared nultiple 8: S.0 Standard error of, est:.nsrel 0,2?2
:
Srror
1'02C
q39
$td
0o*f f icd.ont
6. 5{?
0.01,4
s,
Std
S,S
t$x
s.
hnalysis sf, Va**snee
Surp*of-$quare$ Df U6&n*gEuars
h,
0.010
0-444
krum"r*t.::::li:i;"*
t p{} f*{t}
.
S,{ll S,S0}
I " s00 s,3?$ s. ?*i
{saf folaranca
sls
1
0.
6
0"s?6
P*Ratlo
fr"1{0
p
*,1}1
-i:?ft
$e following results are for:
rtp I{ELL$
var! lNcoNcENg t{: I
I
?6c-,
G15S
-
Hultip}e El 0"!.9? squeirsd *nrltip}6 &; s.$}g
lpusted squared nurtipl* Rl 0.$ $tandord errsf 6f, €rt.\m4tqr $"3]d
Coefflcleni. $td grrsr
std Coef ?ot*rancs I P{f
ftu*,
esustAilr
8.090
T
' $00
*'??3
**. {93
f*&*ti*
s,td3
p
1
"
*, *el
s" s39
Analysie of l'erian*r
0.s34
0"83?
il*i*,*.
rygpg1g6
Sf !{**n-gqu*re
1
0.034
6
0"
r.40
0"s39
***
Ourbin-Hatson
is an out]ler
D Sratisric
2.41s
n;r_:,
t$lI,S
=:=...::
* 6165 ===.;__-''"'
I$e
*0 .
0"053
$r$s-of,*$E\ra.re*
!.
I
o'8
19?
I. {UI
-0, 025
?eS},i
65
=
(StudentiEed Reaidual b
4"
*?Si
Ip Var: LNCONCENT N: 8
I,
F5lrEtelt sguared $Bltiple
l4ultipl"e B.: 0. ??6 gquarad *rjlr*ple e: S.403
8,! 0"F35 gta*dard e.rrpr of es*imet€, il.lp?
eceffi.cient
$td Elror
Std feef ?oler*ne*
s *{? f,&;il}
s,92*
fl,71.9
s.0
9"*?S e"ss*
0. ssz
0,*2-Y
0.??S l,*$$
S"*l*
S"*r*
Analy*i.s of ?ar*ance
I:
$rm-of,*Squar*e Sf Uean-$qu4f,e
lon
0.334
0.220
I
c.3s4
6
$. *3?
f*&4t
j"$
9" Sgfl
s"sf4
r** Hlqlt!r:!{e **,
6T is an outlier
{S*.ud*&!*rsd &e**"dr.r*A o
I**
I
'J,.5'14
lrbin-Tatson O Statistic
S*rpt Ocder &*tooorrelation *0"1.0s
I* f+;lqr'tns res"*lte ar* for:
* g1?s
I ffiI.r,S
pep Ver; hll{fl,lggHT t{; $ $ultip3s &r ff,5?{ ${*ars* m*}*{.p}e gl *.33&
lJustea squared multiple *: tt.?t"l Stand*rd errsr qf sstiffi#*ef S";**
*.
Ffl
{seffi'ei.ent Srd sr.or $td ssa* vsL&rar-q* r p{*
.dr--_
tr.6fl8
l"?31
I[}t"ltT
r
r*
-$.ss0
0.046
S.S
s.$*{
**"974
*.i)*f _l.?ss
Analy*i* {}f vn{i{,|ls*
$pp-ef'$Er:area ff
!(*en-${$c{#
tr*naeiq
y
g.eet:
*"*&s
*.&3?
I
I':':::f,*'
0.
'**ro ,"
I***t"o
tl?
0,6{6
I,?.*slrr*
an
I
0"
6
0. 1$g
ourller
5t?
:, t43
0. &3?
{stud€ntt€sd R*ej"dunr. *
*). ,Lt./l
f;;=i;.;;;;;i;;i""ror:-;:i;;
*#lii"t"n'ul*ilirare
var:
r
Io"tuo
ffi;
llr S
LNCONCENT
Uul"rtpl"e Rr
0.38!
autrtple R; s.1{s
.:quared multtpto fi,1 0.004 s**ndaad ersce *f, esti$at*; 0.:ss
Coef,ficJ,ent 6td Effer
$td eo*f tolera*cs
s 8{fr t*r}}
9, 309
"0,
0"710
0a?
$qr.r*red
0.s
-fr" 3$?
s. 0??
r. g*$
t3, itx
*i.*1*
tulalycis *f, fa*{anee
$ur0-of-Sgu*re,s gf Ues$*Squfrr8 f*Katip
l*..
0.s3?
&egr*a*fun
fr::-***
SARNI!|G
*.215
I
S"S3?
0.036
6
*.3
1"03t
6
*i*
*1.4r1i
Va;: IrN;0tiggil? H; I
ned
,-
ililltiple &: 0,72't $quared msttj.ple ar S.S?3
squared nultiple R: 0.450 $tandard errnr *f *sti,saf*: 0,t.3*
J-
q'd
F"^JLu
Frru!
r .ar.r^lafrr
3'**
i.,
til,*"
[
s*s
s, . *&
!r
(Studentized Residual *
SeF
s"
Std Coet Tolerance
t
p(Z
8.?92
g 0gl
"
S"!19
0.9
i6.94s
& ,*20
* ""tT.t
L "$*rJ
?, FS6
Analysis 0! yasia$ce
9ssl-of,-$q'lrares SF !{€an*Sqtrare f"-B*trf
$,129 L
s.1?9
6.?3?
U.UIj"
0,11$ 6
s.819
Tal,
l,t
0"fi*S
S" S{g
**un*u ***nu
,u an our]rer
*2
{$t1.rde$t"j.ae* &.eeid1:a,:1" *
"239t
2,6*5
fpbin-Tateon B Statistlc
Irst Cl.rder AuEocorrelation *0. 315
-3n€ fgllolt:ng reslrlts *re for;
* €?0$
r t$llS
l, Var; I,X{ONCS$? $r $ Mulrip}e R; 0,866 Sqsarc,S mu}trp}n $.r 0.T{$
Adjuet*d *guared mulriple &: 0.70? $tandacd errqr 4f s*ti.!*atsr fr.}sl
fgeff,iei*nt Sfd grror
$td *.**f {qlsrqnss
t F{} yei$}
*;.
CITs
t
ffi.i
7,$54
s.$61
0,38d
S"St4
*"*
rs.s4s
*"866 1,0fs 4.?3*
Analysis 4f Vari&nqs
$ss-*f*$quare* tlp ilea$-$q1**ra
8,1S8 t
&,1s8
D $Eatr$tic
]urn-watoon
]st Order Autocorrelacion
0.
063
2
""t23
*0 43r
"
6
n n{n
tr*SstA.e
1?.f1?
$"s*$
*"*&*
*"se3
...:.i:.i,.
J
.',.
*orro*rns relurtn are for:
etEtf$
-
q4t
yq
G21S
W
ilultipla Rr 0.?9i Squaxed nulripla Rr S,$?s
0,0 ttEndard err*r xr{ sat{smtr: 0.30S
Std 5rso.r St{ foef t*laransc
t f {f
fi-.il:;.:{:::,.
ftsram
1,X4S
s.s43
l:lll
A$aly$i.s
tr*&etis
sd8 I
0.5s? 6
0.046
s"093
0,31S
s.
ls an outli*r
f.916
$bin-ratson D starisric
l'"
First
Order
S*{}"}
of Vafi{n*r
Mean*$qu*re
$:::::-*rt
,#;
s_l?$ *"*$1
1.000 0.?90 *.{s9
9nm*of,-$q*eree ff
Regression
$allilIlrs **
0.*
8.2fl2
ar;
&,t
109
{Studenri44d Sssidr}a}
i!{'ri;
{.,,
*
#1
r.,i
*s&
*}"St?}
**lu*!;*ars ror,
frrfi[l]-*n{
p€p
Eirr L:eoNefi$? Nr I
xulrtple r{r 0,0t? $quar*d R$lt{pte R; s,*s3
I!-Jurfad rquared rn!:ltiple &l 0.0 $ta$de:d Error of *€tiF&tal 0,;il0
lffect
Coefficieqt $td Error
$td eosf fql.sr*$*a
F|?
c
I
$**'
t
n ollt
s"00?
$, s3{
t"*f$
&n*ly*!o of Var*.an*e
Sun-{}f*Squares Bf !{€an,Sq$sre tr-&stig
:.
Irrc
0.0s0
0"347
*tF!9lon
il;
nn
0.*22
SAgNIl\.t" i*i
XX5
1
0,90s
ls an 0utli6r
s,003
0.0$*
6
{Studentlzed Residual *
,,
695
0"095
tar
1:
v " uu#
*"s$&
S
g_g*s
fi - 33"$:
-l,i{i
r3l"#i::.f,,f"::i*i:t1.''
tlre clXpsing r*6ulte are f*rl
trELL$
-
G23s
f,t var: LIICONCENT N:
8
-'
&dju**ad *gu*r*d nnuJ.tiple
Multlple R; *.69S Sryrer*d multipl* R: S.d?*
R; CI.3SS $ta*d*r* *rsor *f s{?*&sfer S,l:,S
$*d grrsr
f*aff,iei*nt
ilffi,
*ts
Sfd C{}ef
* p{? X&i}}
Ls,#.39 $"&*&
i.,s$& 2,..13A $.& s
T6l*rs&*s
0"{:,3
$*
0.0ls
*.6 *
&r*lyoi* of V*sfgrl*q
Su{s-of *Sqr.:ares pf M*ail-6-guer* f-Ast*e
a o90
s, s36
I
Sour*s
0.s6s r
0.0?3
*il,li":
lrbrrr-*"."on
D
statistic
6
*.*ss
*.&2.k
s.dls
V
*.fi*s
2.333
Order A,utocorrelatr.on -0.d00
frst
THDII*r*ing rerulte ar* fqr:
I
tl: 8 !{ultiple g,: B .222 Sguarect ntilr rpir Ir: fi. U5 t
ied stuared n*ltipta gr 0"{l #tand6#d ssrqr sf qEriwer*r S,f*$
fr Varr
t
LIICONCENT
f€*ff*eiqat
$fd
$rrs{
$td {.qe$ ?ee*.sqr},ss
ffi
ft
:,
Autocorrelation -0.0{l
8.',|42
Y,I
1&f
e ptf
f#e&i
,;.:|i .ii:i
n.ra,.f
;r'l;|::liil]i-,.r:
rl:i
,ll
0rgf;s
s.
*$,0e1
f$9
0. *33
a"{
*$,9s3
Amlyeia of ?ilri{nss
Srrm*ot*9q{*rsx Of Mssn-$qt*s*e
0"0?1, I
$,}td 6
r*t rNU\|ING r**
131
138
;
I
I
I
':i
r
t
t
il
t
:
,t
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;
I
i
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an outliss
en
outli*r
6,SXt
0,&s*
19,t6*
"
1.000
-0.r'
e.&&*
0.1{?
ff*}{ntiea
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{$tudantixsd &asidqq.l *
(Studentlreft Rerrdr,ral *
*fi"ee$3
** esstt
"
LHAn, mt$sffiLvmm
11
1S
"
s
6s
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0gnm*irst*w dffitmin# ts M Mtr
wM
det$dsn h*pf wm
dstrsfrtrsn &npl
f
Sr#
sf thq
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r nS nttrm**M Wspemm"
g
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6
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- s * il fr w @ *d3* * @ @ ry w a
0r _t I r r_r_tr_ | .r_I*Il tJ
ffirtr&&&&&qQ&ffictusqrftntu&
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&dmmf{mrin# ffis*nt
h
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I
t
I
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t
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Monitorirs Pdg lnfonnetion
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23, 000 J,eadr pias,
980{07
98080t
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981^112
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DATE$
961021
970505
9?0714
91LAZ4
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98 0B 04
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22.040 L€ad, *i$$,
23.Q09 Lead, Sise,
?b.0S0 lead, 9i**,
963.*2t
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0.500
diiff:,,."
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2"1.fi9* Lead. Siss,
28.000 Lead, Oiee,
29,00S Lead, ilise,
30.00S Lea,j, Piss,
>av),aa
9S04 0?
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0.26p
25.S00 L*ad,
26,044 L*ad,
9"tr024
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1"***
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2?.Qbt Lead, $iss,
24.8$0 Lend, l)i$s, {
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?9.000 Lead, Sigs,
30.ff0fi Lead, siis,
0. 50c
u, f, /l
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$tandErd Sev
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cor":cEilT&4T10 tr*lf0iicgr{T
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2?.840 Lead, Disg,
24"000 Lead, $i$s"
?5.0S0 tead, Di*s,
26.fi00 Leadf D!ss,
?6, |)fil'l f.aal
nr eq
28.000 Lesd, 0i$$,
29.0AA L*ad, $1**,
30.000 L**d, Ojse,
Lug0$cf;t{T
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1
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1
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-0.693
0,0
0.0
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t*.,
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?2.000 L*ad, Fi*e,
23.000 Lsad, 0ise,
24.000 LEad, }ies,
25.000 tead, Sie*,
961022
9?01 13
9?0506
970?1 4
9? r 0?1
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il?s
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98082X
98t:10
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4,
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26,0*0 !,ead, $i.ss,
??.000 Lead, Dl$fl,
28,000 Lead, Digs,
?9.000 tead, $i$*r
30,000 tead, bi.ss,
98 01 X{
9S 04 06
il?fl
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*0 6&3 u613
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fl, S$id *ql3
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*'rf*;".M*xinun
$tllo*'o
*
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*
fD
0. 500
*0. 693
1,000
0.556
0.16?
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9?07X4
97L&zL
9BAL22
9S04 03
1333
!I of
0. 231"
coNcgNTn"AtI0
ff:i$ffi
Stacdard Dev
3.000
0, 91?
-0.395
1 n21
rB *
1-**S
3"$*S
x"es*
i
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1"S**
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cc'$P0usF$
A?.000 L€ad, 0iss,
24.*90 tead, Oiss,
lb"uuu I,eao, ur.s3,
27 .0C0 l,cad, Diso,
28.**A Lead, 0iss,
9?03 06
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of
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6
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1.099
0. s00
980123
9;09 21
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t''lcollcIbl3
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€10s
c0!4pouNgg
??.000 tead, Fiss,
?4"000 l"sad, Digc,
?3.S00 Lead, 0is*,
26.00$ l,ead, 01*s,
21.940 lead, niss,
24,000 lead, f,riss,
9?0506
ffo8$
0.0
qrn
DA1S$
961 022
ffiI
LNCONCENT
:t
ErqflTf
tr. *ss,
1
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1"&$*
1"*fiS
d
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ugl.3"
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1. *8&
coiqcaNTRATto trNc0licENr
caees
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]{aximum
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standard
*0. 693
500
0.0
1.000
0. 500
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611S
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q11n2A
9801
2i "84fi
t5
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COMPCUI{*$
Lead. Diss,
Lead, 0iFF,
tead, Sis$,
?Q OflO l.s:d
991109
30 , S0
1.*S*
3"**S
Lead, Dlss,
l*ad,
e.ss$;,f
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1"Sil$
Diss,
1.*fiS
?8"000 tead, ilrss,
98 0403
98 0E04
lils
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72,0A0
24.000
?5,0S0
26.000
96L022
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97 fr1 L4
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*$.693 xgl.i
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88
500
6.C00
1.500
? nlq
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Dev
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s6ia22
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9141t4
9'|L$24
980115
98 04 06
98 08C4
98 1111
693
i."tsz
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1 nn?
QTR
G&?i-g$s
CSidpS*?{$$
22,400 tead, Olss,
2
A Ail,fi t.aari
ni
ce
2S.000 Le*d. Biss,
26"000 Lead, ti$s,
21.8q0 tead, Siss,
tS"ilC0 Lead, ryise,
29,fr40 tead, 0i$s,
3$.000 Lsad, iliss,
d
RFqiil"P
]
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t. *q*
l.*&*
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^*.$93 vg/3"
-S,S$3 *ryll
*{.r . 4}3 ug/ }
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CONCSNIRATIO f,}ICONCENT
0.500
0.500
ndard Dev
*
9e TD
AAîr
r
2 tv t Lc
QTR
DATE$
c,oNcgNfftAt:o
0.5s0
0. 50s
colicfiNTRAtr0
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9811 l.1
CONCENTRATIO
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816S
srs
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n;:
rt
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I'q
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I
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tt!{]f $s
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4.000
LNCONCENT
$!ug$$
1..000
1
1.
SS0
"r . UUU
1. C00
1,q00
teadr Diss,
*0. 693 uq.rl
-0.693
-0. 693
-0. 693
*0.693
-0.693
-0. ii93
ugll
qE,/L
ug,/i
ugll
ug/t
ugll.
t. J6b
*0. d33
qTR
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?4.000
?S,000
26.000
2?.000
COHFOin'rD$
Di s s ,
Lead
,
GRItES$
RSSl'I.T
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1.000
1.s00
1
l,ead, Disg,
Lead, Diss,
tead, Diss,
1
Lead, Diss,
2fi.000 Lead, Dlss,
29.0*S tead, Ei.*:,
3S"0it0 Lead, Oiss,
0.500
0.500
0,500
0. 0
.0s0
l'.386 uE,rt
LllcoNcElrT
22
9C
RES{'l,1
.000
I .000
1. S00
I .000
rI{coN08}rT
*0" 693 ugll
-0.693 ugll
-0.693 ug/l
-0.693 ugll
-0.693 ugll
$l{IT$$
-0 ' 603 ug,/l
-0,693 uglL
-0.693 uq/1
TNCONCSNT
-0. 693
-0. 693
-0.693
0.0
QTR
22.000
24"000
25.000
26.000
??.000
28.000
?9.000
30.000
COMPOIJND$
GRTLSS$
RSSst?
l",ead, Disg,
T,ead, Dies,
tead, Disa,
t".900
1 .000
tead, Diss,
Lead, 9iss,
lead, Fiss.
tead' llt33,
i
I,ead, Diss,
.00s
1.0c0
1
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1"000
1.000
trNC'ONCENT
-0. 693 uq/l
IJ}II?S$
ugll
uq/l
*0.693 ugll
*0.693 ugll
*0. 693 ug11
*0.693 uq/l
"0. 693
"0. 693
-0.693 uql1
LI|C0NCEBt
Rg
lgffilnu$
Jcaximun
.rrt13atr
f;;.
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1.000
Lead, Diss,
Lead, Diss,
tead, Dis*,
0. ?35
cotJcENTRAfIO
ib66a
vq-tv
'$tEndsrd
6RTtn$$
lead, siss,
L.23'7
DI{TE$
961112
9?0508
970714
V1LAZQ
980i23
980402
980804
9811X1
ffl75
Co!{PoU$D$
Lead, Diss,
Lead, Dies,
Lead, Diss,
-0. 693
CON{;EHTR}J:O
3
COr.rFo$lrD$
693
0.500
4.000
0.93?
sAl$$
961.t1.2
9?0508
9?S?14
971020
9S0123
980{0?
9808S4
9S1111
Gl6C
ff,
tead, Diss,
QTg
9?1S20
9801?3
980406
980821
'f;ii
I*
-c.
??.000
24.000
25,000
?6"000
2?.000
28,000
29"000
3S.000
97tJ'114
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s'*,
-0. 693
-0.693
D&IE$
961111
9?050?
ii"".
Se\t
Tn *
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#
#
k!w(
I
0.500
0.500
0.500
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1
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QTR
ffi:;
L,l::::::::::::::::lc${cn$T u!{
-0.693
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t$$ffi
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m'
@
I"}ICONCENT
0"500
,
ir;
25.00Q I,ead, Diss,
,::.g..gf cases
:.
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W
-0.693
*0.693
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0.0
0. $00
l{rxl"eus
e*
I
8
0.500
s.500
0.500
0,0
-0. 593
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-0.693
0.0
QTR
COMPOUNP$
RESUI?
LNC0$e8N?
UNITS9
ks
'qtis
961 I
?2"000 Lead, Dles,
e4.000 I,ead, Diss,
?5.000 tead, Dlss,
26.C00 lead, Dies,
:?.000 Lead, Diss,
28.000 lead, Di.ss,
29.000 Lead, Diss,
30"000 Lead, Diss,
9? 0?
lil
9?1020
980?03
81sS
*1!
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980{02
--.
F:
tt
9?0508
98 08 0.{
r-
981111
I .000
1.000
I,
UUU
I .000
I .000
I .000
1.000
1
.00c
r
-0.693 ug/l
-0.693 ug/L
0.0 ug/.l
*0.693 ug/l
-0. 693 ug/1
-0. 693 ug/1.
*0.693 ug/l
-0.693 uE/1"
f;
t:a
i,
*
CONCENTRATIO I,NCO$CENT
n*
0.500
t " 000
0. 5 6?
0.1??
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r
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Dev
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r
-0. 693
0.0
x-
0.245
ir
-0. 607
t1
$sasssBs*ss
QTR COMFOUND$
tead, Siss,
DA?S$
22.000
961. L 1.2
?4.000
25.000
26.000
??.000
9? 0508
9?S7 1 4
9?10?0
qnn?n?
9A 111
GRILTS$
I
RESULT
1
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r.
Lead, Diss,
Lead, Di.ss,
c00
2. 000
tead" Diss,
tead, Diss,
1.000
1 ,000
?8.0C0 Lead, Diss,
29.000 Lead, Diss,
30.000 l,ead, Diss.
98 04 0?
98 0804
*ii
t,
1.C00
1.0c0
r.000
TNCONCA}iT
-0.693 ug/I
v.vrJ
et.
UNITSS
L
0.693 ugll
-0.693 ug/i
*0.693 ug11
-0. 693 ug,/l
-6. 593 ug./1
*0.693 us/l
CONCENTRATIO ],HCCNCSNT
1Ji,.xi...
t{axir,run
fiilo.'o
o."
* Cage ID *
q4111?
0.500
2.000
0.69?
-0. 693
0. 530
0.490
QTR
DATN9
t;
981r"
1
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'FQ'TT
.
.
t*ad, Diss,
28.000 tead, Dlss,
29,000 t€ad, Oiss,
00c
.0c0
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.000
8.000
30,000 Lead, Diss,
CONCEI,ITRATiO
000
.000
27.000
3
+
.000
25.000 Lead, nlss,
26,000 Lead, Diss,
97 102 0
98 02 03
98 04 02
9808 0 6
c?0s
COMPOUND$
22.000 I,ead, Diss,
24.000 lead, Diss,
9?0509
9?0?14
G?0s
0. 693
-0.520
LNCONCSNT
UNITS$
-0. 693 u9/1
*0. 693 ug/i
-0.693 uq/1
*0. 693 ugll
-0. 693 ug./1
-0 ' 693 ug,/I
-0. 693 us/1
2.0?9 ugll
:,NCOI'ICEI'IT
8
Q,:i*:i...
M€an
f:"::-::":::
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'
c?1s
0.500
8.000
1.43?
-0.593
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0,98C
DATE$
9?0508
970?14
9? t0? 0
l;ii
G21,S
98 0?03
98 04 03
ffil
980805
I B 1113
?.0?9
*0.34?
QTR
COt4pOUNtj$
72.404 tead, Diss,
24.000 LeaC, Diss.
?5"000 Lead, Diss.
26,000 Lead, Diss,
27,000 lJead, Siss,
28.000 Lead, Diss,
29.000 Lead, Diss,
30.000 Lead, Diss,
UKI !gJ+
1
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t.
$00
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1.000
1
1.000
1.000
1.000
1.000
I,NCONCENT
UNITSS
-0.693 ug/)-0.693 uE,tl
*0.693 ug/I
"0 ' 693 uq,/l
-0.693 ugll
-0.693 ug,1l
-0 " 693 ug/1
-0.693
ug,/1
CONCANTRAT:TO L}ICONCNNl
8B
500
0.500
0.500
0.0
0"
Slri;r*"""
ffean
-$tandard
Dev
*0,693
*0. 693
*0. 693
0.0
I
F======== *
Case ID
-}
c2?$
DAtE$
961113
9?050?
9707 I 4
971021
9S 0I2 3
S::fur*"'"
COMPOUND$ GRTLES$
24,000 Lead, Diss.
?5.000 Lead, Di$s.
25,000 Lead, Dissr
2?.000 Lead, Dlss,
28,00C Lead, Diss,
29,AAA Lead/ Diss,
30.000 Lead, Diss,
9A0403
JK
OTR
?.2.404 Lead, Diss,
980804
9911rC
CONCENTRA1IO
ao
c. 500
0.500
LNCONCSNT
*0. 593
-0.693
R8SULT LNCONCCNT
1 .000
-0.693 ug/l
1.000
-0.693 uE,/t.000
.
c00
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1.000
r..000
, r v.,1
st,
L
-0.693 ugll
4Oa
-fiv. _JiJ
.'^/1
sy/ {
-0 " 693 ug,r
-O Aa? 'rn /
I
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*0.693 uE/l
U}II?S$
iJ
k*e""a
0.500
p*,.
0.0
Qfrr
DATU$
coHpoulto$
f!is,
; ,a 0is -,
25.00C Leaci : ss,
?2.000 l..1dr
?4 .
9?0?1 4
9801?2
980406
980804
981110
coriciNTiATIo
I
0.500
0.500
0.5cc
0"0
GRTTES$
t)00
25,000
27,000
38,000
29.000
30.000
9?1021"
#::i:::,,..
{.
:r
96r.113
9?0507
o,
l*l{ininura
"u"*u
-0. 693
RESULT
1.000
1
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1.000
:,ead, Diss,
Lead, Dissr
Lead. Diss,
1.000
1.
"
000
L.000
.000
1.000
lead, Diss,
1
Lead, Diss,
LNCONCENT
-0.693
*0.693
-0.593
-0.693
-0.69-r
-C.693
I
UN]TS$
ug./l
:F
ug,/}.
ug/I
ug/]
ug/i
.4
l"
ug./l
-0. 693 ug/1
-0. 693 u9./1
i;
i,ir
I,NCO$CENt
a
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-0. 693
-0. 693
-0. 693
0.0
;'i
**s**sEF*s
*r!.-.
G2{S
'o.
Q?R
L1AlE9
9?0?1 4
2 t iuli
9801 ?2
G24$
*ii
980403
98 08 0.1
e34$
981t 10
CONCENTPAT!u
1,ff-ri"."
l{aximum
I
I
I
I
t
t
t
o-.'
LNCONCENT
U
a
0.500
-0.693
0.0
-0. 60?
0.2{5
i.000
0"562
$illo""o
CO!{POUND$
2?.000 Lead, Diss,
24.000 Lead, Diss,
25.0C0 Lead, Diss,
25.00C !ead, Diss,
??.000 l,ead, si$a,
2S.000 Lead. Diss,
29,000 tead, Diss,
30.000 Lead, Diss,
961114
9?0507
0.t??
GRTIES$
RESUIT
1
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1. C00
1.000
i.000
1.000
1.000
I .000
i.000
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I
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13
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ndju8ted
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tn,
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r f{* t**t}
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29.X89
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p
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f
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Anal.ysio of, Variafice
'l;*.,
Mean-$quare f-Ratlo
303205, 5{5
1 303205.545 6, 90?
2633S1^,955 6
43896.992
Swa*of,-Squares DA
i*Eraspion
0. s39
I:1::11
Ourbin-Watsan D
Stati8tic
1.904
Otder Autocorrelatj.on *0"090
Irst
!" ,o**o,nrng resurrs are ior:
HELL$
- cL6s
ffi :::::::T::-,,:'.:, :."::::.1;-'.lll, .:::::::::T;:,:;
Ifffeet
coef,ficlent
t*srA'{?
l;"'
r:
turce
&egr:6osioa
1".
'71tr'#;
$td goef TcleraEee
t
*-
F{t Tait}
'*i?"?ll -3.3r, r.ooo -8.tll $:l}?
AnalYsio of, variance
I.
I
l::*::
t** fftNlllllilg ***
std Error
-
Su$*of*Squarea DF Mean*Sq$are F-natio
?:.905-545 I
955 6
651181.
71
is a$ outlier
?1905.143
X08530.3?6
F
0.663
A"487
*
?.?**}
{$tudentized Rea{d$al
*:l';l*'1"?":::::i:;i"" -i lli
fe foltowing results are for:
ecEr,rs = GrTs
I v;r; C0$CE}ITRATI0
9e?
I Multiple ar 0.624 sguased multiple &r 0.3frs
squared roultip:.e 8: 0.?88 Standard error of estLeare: Zg9.oil
lj"ut"a
Coefficient std Error Std Coef Toleranee t p{Z t*il}
tfect
4L68.446 rtzl.846
0"0
3.?16 S.810
"
*1"956
42.34b
-82.832
-s.624 1.000
s.*9E
ssfAr*?
N;
Analys;s of Varianse
Sun*of,-$guare* Pf' Msan-$qlrare f'*8atio
,ffi]**'"
fletidual
r'
I{NlNlH0 ***
342200.41L I
s3656?"469 6
3d2200.931
8943L.245
3,826
0.0E&
ls an qutlier
I Stat{sttq 2.685
{Stud€ntised Resi*.ral *
?9
first
Autocorrelation -0.369
folloning results are for:
* G18S
Order
Fr:
'
3,6931
*rl:
,..
l
taslsd'
SJfest
l{r I
Hultiple Rt 0.150 Squased multiple R: 0.023
equ*red multiple R: 0.0 $tandard effor of, estinate: ?89.rnz
eoefficient $td Srror
Std eoef lfq.Lerance t
Ptz Taill
COXCnNtRA?I0
3t10.?2?
*15.288
ft'-*r
1i186"699
41.0r8
0.0
150
-0.
1
.
2.955
.000 -0. 3?3
0"0?s
0.722
tuialysis of Variance
t*.*
Su&-of,-Sguareg DF ttean*Square
r1657. ?68
503{9? " ?3?
1
6
1165?.2$8
83915.45s
f-Ratio
0" 139
P
A.122
rr$ii.:
Statietic
1..935
Autocorxeiatlon 0.002
Jst
le foltowing results are forr
* GX$S
nOIlX.$ I
Multiple R: 0.184 gquared mutt{ple Rr 0.034
fr
T Var; CONCENTBATIo N: I
IIEjusted
squared multiple R: 0"0 Standard error of, estimetei 92:..410
Coeff,i-cient Std Error
Std Coef lolerance
t Ptz fail)
9422.356 3455.613
0.0
k.'126 0.034
130.4?3
-59.900
1.000 -0.459 fi.662
orR
-0.1e4
A$alysis of Varience
gEm-of-$quares DF l'{ear:-Square
El
F-Ratio
P
l.?8950.501
1 17895S.501
0. e11
0. 66?
5094199.499
6 949033.250
Ourbin-$atson D
Order
ffi;:'
.
$i:iii-:
ir* nNllllNg **r
(Studentized ResiduaJ. *
95 is an outlier
Ase
3. 956)
D Statisiic
2,713
Jrbin-watssn
Fi.ret grder Autocorreiation -0.395
foilo-'ring :esuits are for:
* G20S
lffltl$
!'lultiple Rr 0"13? Squared &ul"tiple R! 0.019
Dep Var: CONeCN?RA?IO l{: I
ljouauA sguared multiple X.: 0.0 $tandard error of estirrate: ?22-084
Coefficient Std Errcr
std Coef ?olerance t p{z
ilr."a
2944.687
833.118
0.0
.
3.05{
9.fi22
lrys?Asf
*0.t3?
3t"447
-1 0.552
1.000 *0.339
0. ?d6
r-"
Anaiyeis of Variance
p
$un-of *$quares DS' i.6ean-Square
f-Ratio
trllcce
LdLLI
5658.6?8
I-*-oaJ^*
295928.822
Fesidual
t{A*}trNG
**,
is an outl*er
t,797
tson P Statistic
st Order Autocorrelation -0.001
The f,oll,owlnq results are for;
* G21S
vr6tI,9
105
Var:
COUCEI,ITRATI0
llr I
I
6
0.115
5658. 6?8
0. ?46
49321.414
istudentieed Residual *
Multiple R: 0.2&l
$guared
2.299t
nultiple Rr 0"0?9
is an outlier
n-I{atsan D Statigtic
2,.649
*0"4{8
tXl.
ft
{Studentised Residua} *
2. ?80)
t 0rder Autoeoffelatian
following resrrlts are for:
rTll.i
= G?3s
ID€p Veri CONCEIIfRATI0
lll 8 Multipl.e R: 0.161 Sguared $ultiple R: 0.026
squared eultiFl€ R: 0.0 Standard errar of estimat€: ZZ9.?02
Coeffic:ient Std Srror
Std Coef Tclerance t p{Z Tail)
3653. ?34
862. {{4
0.0
d.?36 0.005
-13 " 033
32.554
-0.161 1.000 -0.4e0 0.?03
Anaiysis of Variance
p
$um-of,'Squares DF lirlean-square ['-Ratio
8471..1?8 :.
84?1. L?8
0.160
0. ?03
ff::",.,,
R*sidual
3L''\28 .822
6 $2354.904
ff='*'
t-.
***
|FF
':.,'
-8,NIlrlG
Blrbin-Watson
ts an outlier
D Statistic
3,525
119
{studentized Reeidual
*
Z.{04)
Order Autocorrelat.ion -0.?59
Jst following resui.t,s are for:
tlte
* G23S
ITEll,$
*r Var: COI$CSNTRAfIO ti: I Uul"tiple R: 0.34b Sguared multipLe R: 0.11.9
Adlusted squared rnultiple R: 0.0 Standard errar of estimate: A99.50g
Ifaâ
Coeffici.ent Std Err:or
Std Coef tolerance
r p{2 Tai.l)
;{AITAil'?
603.183 1123.551
0.0
0. $3?
0.611
38.221
42 "4IO
0.345 1.000 0.901 A . $2
g.
Anclysis of l,iarla$ce
II.
l-Fur"*
Sum*of-$quares DF Mean-Square F.-Ratj"o
P
7?,857 .926
1 ?285?.926
0.812
0. 402
538?29.5?4 6 89?04 .929
fiii;i::
l;!l $Aar.lrNG *** i" an outlier
lJg
]e
I3l is an outlier
Iee
*rrrbi$-Itatson D Stati.stic
2.452
{gtudentized Residual *
{Sturlentized Residual *
7,
.7
47',t
-2..8241
t S!d6r Autocorrelation -0,415
following results are for:
Coeffi.clent
239S.821
uulriple Rr 0.464 Sguared nultiple R: 0"21.5
0.085 Standard error of estimate! ?.'15.672
p(2 Taill
Std Frror
fjtcl Coef ?olerance t
103?. 895
0.0
2.3r.1 0. 060
*&s"fiss 3*.&s& *s,*s{ ["e&s *s,*s]
frnc&ll**a
iNp.ff
?snt$&$fe
S *s$*Sffi*re,e mf ;q#*$!-Sqr*ese f***'{44}
:s&&&&&.ftpa & 3"*6ss$-Rs* &"s4?
*$s&*$,?$s & ?6&&?.ts$
&q$ry
l.$ff ;'i* &n s6fl*";ir,.f,
& S {* *t} ,s'*c,,h3*.s
kymmrm***r;ffi*
t
t'
n
-I
!F
il
il
il
t
il
il
il
*
t
il
.$:$*$
s.a4?
{i*{ieder4t*,ew* 3*aS&lx&
4#u*S*m*ised
&sxi&lai
ry
*
p
s. *41
*6.S9g}
t.:S1}
-'
Dlssslvfis*
Jaamsa,
I
r G#{$,
I
*'q13
AF|D
Gl{
apffias$xot{ vnh$68 r+R Ln OF COSCe$TftAsr$fi
SID ilQ{ qfin}**8, ril$S, l*$ R*g*E$StO$ e$eiy$i$ **g }BR3SRHED
$&iilil#* I&s$ ?nAN I QlrA&t&*s, tgfis" s0 RncRnssioN ANR:,YSIS
G08$ A}rD Gl 05 {i&& BAflX
fu*'*n'=i.iultrre
I
rc::
il! Yer: LH{ONCf,}n *l I
Uqltip:.e *.: *"161 $quared su}sipLe R.: 0.026
FFJu*ted *Eu*red rtul,ri,p1p K:
coeffrclenr
fr"3r1
*"s*?
Jcct
*stept
w
I
#,txce
fill:[**r
YA&!{X!&S
*-0
$t*cidard
scc Errei
*rrsr of e*t:i.satE: S.llg
sid coef Tolerarrce t ptz Taill
0.0
ag.bsb 0.000
0.1s1
1.**S S.43a 0.6?9
*.3*g
0.s11
Analy$is cf i'*r;i.an*E
$$**ef-$quare$ Sf Hae::!-square
0.*s3
s. s98
***
f*bin-flatson
3
?
g rs an $u{i"ier
$.*93
0.014
p-Reeic
s"is6
0.6?9
*
-2.t3S)
{StudentiE,€d Residua}
D St*ristlc
1.940
f$.es*. SNdsr A$q{}4d}xsei"etisn *0. 1It
*":"i$iusra ror:
]*nr**"**n
gsri f'!*C*&l*Cl{t !{r I
F{ultipte R: 0.1S3 Squa{ed rnultipte R: 0.0i1
X3t}*t*S eE{c&re* m*!ttrp}.* *,r 0"0 3t&nd.&rd eiror cf e:tir*ate: C.1*3
&e{&
&ffe6*
-
ryS!*f
t
f$*fficieni
fi . s*3
r).ss{
t p(? Tail)
22 .915
0.000
1.0s0 0.??5 0.?92
Std Co€f toleranc*
0.3s?
s.0
0.01$
0.103
&&6:y9is sf varianca
guia*$f*Squarss SF Uea$-Sguare r,*Rat.io
tr*re*
*.
[Eiler&{Ab
*ryg*${***!r
*$i.
I
n n?q
**s*,d;*El
[;;;;".:"-"-'-q*ss
Std Srrsr
0.001
n nxl
a
s.
0?5
p
0. ?92
ig an outgj.er
{Studentised Residual *
4.364}
?.?46
&io-Satson D Staristic
3** Srd*r &st*eorrela{.i.on -*.?16
31ltm fq}}$rfing rssults are fcr:
* 6S55
*8}*f,$
V*rr &Xe$liegilf $: $ $tuJ,ti.ple f,: $" 181 Squared ilruttipte R: 0.033
ftS$$st** squflr€d rnultipi"e R: S.fi $tandard error of eetimate: 0.096
p(A Taj.t)
{o€f,ftcaeni Sld Hxrsr
IS**t
1"3
8.401
-$.006
qsws?*8?
c.3?4
s.01?
0.0
-0.181
?5 . t9?
1.000 -0.450
0.000
0.668
Allalysj.$ of, Variance
Sxa*of-$quaree !F Mgan-square
SEU;ce
0.002
0.0{3
ic an outlier
1"395
n!,rrbin*slets$n S $tatistic
Srder &str*qlcrel&tisn S.S5?
19
fol.lsx**r{ resu}ts are for:
I
5
0.00?
0. 007
F*natio
0.
?03
{gtudentized R.esiduat
*
p
0. 668
*2.518}
St&S pERroRplED
Yrrt
G06S
II
e|{f
.t*t
ltultiFla R: 0.008 Squared rnultipte R: 0.000
lueteC sguared mu-ltiple Rr 0.0 Standard errer of, esti:Eate: 0.A50
L:{CONCANT
N: I
Ceefficieat
f;|e
E
gflGlNr
D
Std
Arror
Std Coef
:ffi
i-i
i1"4t
p(l f,ail)
tolerance r
?.130
-0. soi
Sum*of
Iurce
frresslon
**eidual
0.8S5
0.0
8. 054
0. 000
0.03{
-0.008
].000 -0.020 0.985
Analysis of yarianee
p
-Squares Df lfean-$guare F-Rartio
S.000 I
0,00Q
0.00C
0.935
0.3?5 6
0.062
*btrn*tlalssn * statrstic
1,1e5
fir*t $xder *ulacorrelatisn 0-325
-f folloring results are for:
= G0?s
I rfElr,s
qfp Var: LNCONCFIIT N: 9
Multiple R: 0.6?0 $quared nultiFLe i<: 0.449
|juxti:d squarad *ultiFla R: 0.370 Standerd error of estj;nat€: 0.3L4
-
*ff*et
Coefflcient
Std
1
3.3?0
0.09?
$srxn
grror
nqn
0.041
Stci Coei: Tolerance
U.U
0.670
.
1.000
t
pti.i
J.IU5
2.389
Tail
)
0.015
3.048
Analysis cf ltariance
F*
0.562
*lean-Square ['*Ratio
1
S.562
5,106
u. o6v
I
Sum*of*Squares DF
ffi{ffii*
ffi;:::
te*q
El*e
41
43
ls an oatlj.er
is an outl.ier
P
0. 048
0. 09&
{Studentized ReslduaL
(studentized Resi.dual
*
-
3.?81)
-2.25?)
I
t::i';:;::'1"?":::::i:i:""
i:?33
foilowing results are for:
lc
a cr IS
r ItEf.T s
$ultipie R: 0.0?t Sguared rnultiple R: 0,005
fStr;*e* $quaued muLtiplo Rr 0"0 standard error of estimate: 0.135
ptz roiI,
ilfect
Coefflcient Std Srror
n Rna
7.521
0.0
1{.824
0.000
U. UI3
-0.0?1
-0.003
1.000 -0.1?3
0.868
Analysis of Varlance
$urn*of,-$quares Df 3{ean-Square f-Ratio
v
0. 001
i
0.00L
0. 030
0.868
x:::*,."
Sp t"er: WCSNCAII? N: I
r**'
u.ilu
Xoaid*n1
f'"n^*"t*o
"'rr
,." an our.rier
o
0. 018
(Studentized Hesidual :
-2.08?
)
0.88f
lrbin-icatson D staEistic
Irsr order Aut.ocorrelation 0,402
!
Thllllowin,o results are for:
* Glzs
_fLS
I*
]
Var:
LNCONCENT
N: I
Multiple R: 0.0?1 $guared nultiple R: 0.005
nultiple R: 0.0 Standard effor of esttmate! 0.11?
coafficient std Elror
std Coef Tol"erance t
Adj$gttsd sgr:ared
fr.-o
pt2 Tail,)
trr*.i
"i-!
,}
;ti
.Ft:I
+-J
fs.\
lFFf
$'dr
**t
r{yi
..
f-w
8.100
0"
0. 003
i|38
0. 01?
0.0
0.0?1
x8.508
1.000 0.1?5
0.00s
0.86?
w
Sr&*gf-$quare$ DF llean-Square F-Ratio
F'
0.000
0.082
,
1.
0,
5
0"014
000
c.
0-?1
fi,ui
P
ti
0.861
k
ff
ii*t
\fl
tna*
Dtrrbin-Tatson D $tatiseic
1.5{3
lr$t Order Autocorreiation 0.088
]
M
foii.ouinq resuirs are for:
xsu.$
] var:
lj,rsteA
F;
L*
ics
a tllic
'iir
p
6 !{ultiple Rr 0.691 Sguared nultipie R: 0.4??
sguared nultipie R: 0.390 Stand8rd errcr of estimare: 0,252
eoef.ficient Std Frror
Std Coef Tolerance t, p(Z Tail)
I . SS?
0.9{t
0.0
9. 388
0.000
*0.08{
*0. 691
0.036
1.000 -2.340 0.058
Analysis cf Variance
Sum-of,-Sguares Dr, Hean-square f*Ratio
F
0.349 i
0. 349
5.4?6
0.058
0.38? 6
0.064
LNCofiCSNT N:
ryi$il:
2.S78
l*btn*l{otson D Statistic
Irrt Order Autocorrelatior. -0, 126
tha fo1l,onirrg resuLt$ are for:
* S16S
Sg:,$$
l
S lttutttpLe Rr G.33? Squared mu]tiple R: 0.ll{
oquared nultiple R: 0.0 Standard error of estitrrate: 0.1I0
coeffici"errt std srror
stc coef rolerance t F(? Tail)
ffect
-|llEErlSEANf
8.346
0.413
0. 0
Z0 .ZO4
0.000
*0.0x{
0.016
*tR
-0.33?
1.000 -0.8?8 0.414
p
SsErce
$um*of*Squares Df Mean-square f'*R*tio
0.0s9
1
0.009
0. il14
0. ??1
0. c?3
6
0. 012
It,
-tF
*d*i&gted
LIIC0NCENI Nr
I
2.993
Irbin-natson D Statistic
llst Order Auiocorrelation -0.581
f,hE f*llo*iilg results are for:
* G17S
I Sgtl$
Ip llar: tt{CctlcEt{t !.1: I $ultiple R: 0.645 Squared multlF}e R: 0.{16
squared nultiple R: 0.318 Standard error of estinate: 0.138
fl,{ustea
Coefflcient Std f,rror
Std Coef Toterance t F (2 TaiI)
ff""t
cslrstAlr?
8.646
e.518
0.0
16.6?9
0.000
*0.645
0. 020
-0.040
1.000 -2.065
0.084
Analysie of Variance
$il
Sur0*of*Squares DF |ilean-Square F-Ratio
I.c
0.081 1
0.08i
Icr6$sion
tr. UtsiI
4.?.56
f
0.
l*
Ige
ti#
'W
[,*
ilDE[?Un
il.s
6
0.019
*r*
79
is
En
outlier
(Studentized Residual *
3.584
)
r
rD St,atistic
-bi,n-natson
first
order Autocorrelation
-
J-fil**'"n'":'lii=are
r,:_
2.674
-0.36?
ror:
-Iilrt
tl{g0NCSNT Nl I
Multip}e R: 0.163 Squared multiple R: 0,026
I
liustEd sqlrared nultiple R: 0"0 standard error ef estinate: 0.104
Flfect
coeffici*nt
std Error
std coef folerance
t p{z rail)
8.e9?
0.3E0
0.0
20.?69 0.000
IFSTRNT
v
*0.0s6
T
0.01s
-r)"163 t_0$0 *0,404
Anaiysis of Variance
*:::,-,.
**-T;;
"*-"-T:;:" ':
*esidual
0.065
6
-::,:
0.011
0.?00
l.",oo
fellotring i€sults are for:
l{gtl$
= €19S
Var: LNCONCENT til: I F4ultip1e R: 0.199 Squared nultlpte R: 0.040
fe
*u:tea squared rnultlple R: 0.0 Standard eruor of €sti$ate: 0.112
Sffect
Coefficlont Std grror
Std Coef ToL€rance t
F(2 Taill
9.169
0.418
0.0
2Z,St7 0.000
lNsrAr,rf
0.016
-0.008
1.000 -0"497 0.53?
-0.199
IR
Anal.ysis of V:riance
p
Su:o-of-Sguares OF Mean-$quare F-Ratio
3sg ression
0.003 1
0.003
0.241
Q.63'7
i"dual
0.0?5 6
0. 012
T
qasa
YAIIN1NG
rrr
is an outlier
2.?40
lrbin-HaF-son D Statistic
Irst Order Autocrrrelation -0.413
?he followinq results are r-or:
I rells
ilp Var:
flustea
!f**t
-
Coefficient
?.854
*0.005
3.480}
0.0
Standard
Std Error
error of eetirnate:
on
0.
0.
C.0?1
0.098
Tol-erance t p{Z Tail)
0,0
t1.34? 0.000
*0. 147
.000 -0. 363 0 .t7g
Std Coef
0.368
0.014
Analy$ls sf Veriance
Sum-of-Squares nf Mean-Square F-Ratio
Io|rrce
l'
*
N: S Multiple R: 0.1{? Squared nulrip}e R:
squared muttlple R:
*s$l$lr$rf
KrEslqusr
{$tudeatized ResiduaL
GZos
LNCONCENT
I
Ioress.t
95
1.
001
058
1
6
0.00:.
0.010
0.
1.32
'**
(studentiaed Residual *
l"* "Ar*1*6 105 is an outl.j.er
1.?63
Drl-natson D Statist.ic
Autoconelation
0.011
ord€r
lFlf
I
!t* fo}lcsring result.s are for:
sgL!$
- cZls
lp i'ar: LI{COHCEIST Nr I llultiple R: 0,31? Squared multiple R:
p
0.729
2.133)
0.101.
td squlred nultiple
R:
Cqeff,icient
0.0
Std
f; ?1?
-0 ,01?
T;'
Standard
grror
0.561
0.031
error of, estdrnate: 0.150
$td Coef, ToLerence t
0.0
*0.317
iil
F(? TaiI)
14.s50
"
*0.819
1.000
0.000
0.4it4
t:::,,""
0.c15
0, t34
Rasldlral
1
0.015
6
s. 022
{r
b
{;
Sirm-of-Squares Df Mean-square
6
lli
F-Ratio
0.671
P
0.44C
f*
&
F
13.e
(Studentized Residual is an outlier
2.388)
2.605
*b{n-ttEtssn D Stati5tic
Order F-utocorrelation -0.44C
-Et
tla f,ollouing results are for:
wEtL$
- G22s
I
I vur, LNCONCENT N: 6 Multiple R: 0.15? Squared nuLtiple R: 0.025
ndiusted squared nultiple R: 0.0 Standard error of eetlmate: 0,069
goeffj.cient Std Error
Std Coef Tolerance r P{2 ?ai1!
Teet
cobl$?A|rr
8.203
0"259
0.0
31 . 643
0.000
tIt!{
0.010
-0. 004
-s. 1"5? I . C00 -0.389
0.?L1
111
f
Analysis of, Variance
Spures
$uur-cf
*xxi"'
11$
ls
-Squares Dt' !.tean*square !.*Ratio
0. 00L
1
0. 001
0. 151
0.029 6
0. 005
sn orJtlter
I&rbin-nalson D gtatistic
st
Order
Autocorr€lation
{St$dentJr€d Residual
*
P
n ?1
1
?.?3?!
3.530
-0"??L
following reaults are for:
* Gl3$
tlgtL$
var: tNcONcENT N: I !{rrLtiple R: 0.3L6 Squared multip}e R: 0.100
f
J3usted squared nultipl.e R: 0.0 St.andald error of estinrat.e: 0.!.?9
gff,ee*
Coefficient Std Srror
Std Coof iolerance
t p(? Tail)
6.S26
0.6??
0.0
10.152 0.000
,J.025
0.021
].**,
0.316 1.000 0.815 0.446
Sr]m*gf-Squares DF l.lean-Sgtare
$,,-SegFession
0.
**a lqalu{I}le ***
021
is an outlier
is an outller
ilrbLn-tfat8on 0 Statistic
2.32e
Flrst Order Autocorrel.ation -0.363
f,olloring results ate for:
flfl$e
3e
911$
130
131
*
S24$
l.
0.
02r
F-Ratio
0. 664
=
=
r
0.446
2.3i.3)
-3.
01?
!
*
s
I
i",
,
s of variance
{$i:: : !'il
,, outr.ier
I J"**t*n "ir,Statistlc
an
Purbi,ntnat*an D
l.?44
orter Ausocoffelation -0.15{
f*t
I
i
I
t
I
I
t
t
il
t
T
t
I
lr
I
DF
I
t{ean-Square
F-Ratlo
0. l0?
1.696
P
0.24L
-l--------l:931
{studentieed Resi dual.
*
-g.286)
I
lr
I
I
I
I
I
I
I
r
I
I
t
I
I
I
-_-
I
MERCURY, DISSOLVED
0.8
€ct
* Concentrations
determined to be below the
detection level were estimated as half of the
detection level for all statistical purposes.
0-6
J
-l|
c
oo
I
o
I
04
E
r
loo
I
rlr,
I
I
ltl
-fll
o
o
c
o
*/r
(J 0.2
ilu_
0.0
o ro
il
_Ll
_
____n
,t rttttt_ttll
"S,$fo
Monitoring Point
I
tr
PcoriN City/County Landti[
Moninftg Point lnformrdw
Anrad Reon
Drily Arsociates. Eryincers, lnc.
Pcoris Champaign, tL
1999
MEnCUnY" CI$SOL
I
I
I
I
I
I
I
n
I
I
I
I
I
I
T
lo
I
NAiNA
I
I^
-1-
t
I
I
I
I
I
I
MFRCURY, DIS$OLVED
-
n
I
T
I
t
I
I
II
r
-
I
!llffil
G03$
G02S
G04S
G05S
G06S
't1
'+{
"{{
o+{
orl'..iF+Fl
oofg*,
lE5*tdnrlt$
eil?s
G12S
t1
ill
"+{
o'l-*-J
rrl-ffit
roL*LH+,
xaErllattrrr
cfts
G14D
:I-*l
il1
.+l
ll
",1
t
I
I
{
tn6lattrrri
ei?s
G21$
G22S
!1a!ffi|
I
{
I
g
,*|
""t
"+{
"+l
"'L--J
ooL%*J
nzahtrttra$
G24S
I
|*r"rr*"
*
Case
s03s
REsur.Ts FoR MERcuRy, Drssc'vsD
ID i
rt'ta
II'F
uurn
DATN$
961021
9?011.3
9?0505
9?0714
971024
98012?
980407
980805
98111:
QTR
42.000
43,000
44.000
25.000
?6.000
27.0C0
28.000
29.000
30.000
1,;,
COUPOUND$
GRTIESS
Hef,cury, Dis
RASUI.T
0.2c0
t{erculy, Dis
0
Mercury, Dis
.200
0.200
Hercurv, Dis
t'tercurlr, nis
Mercury, Dis
Mercury, Dis
Mercury. Dis
Mercury, Dis
0. 300
0.200
0.200
0.200
0. 200
0.200
LNCONCEN?
-2.303 ug/J.
-2.303 ugll
-2.303 uql}
{4r
UNITIi9
'*\,
M
*1 204
"
ug/l
-2.3CJ uq/l
"2.303 uqlI
{i
"2, 303 ug,/l
*2.303 ug/l
"?.303 ug/l
;1:
's,
I !{iniRum
o,
""uuu
jili::-
CONCENTRAT:O
99
0 " 100
0.300
0.L22
0.06?
"""
I,NCONCSNT
f1l
-?.303
'{r
*1.2C4
i*,*,
-2. 181
0. 366
!<#*g*36As
f Case ID *
l3s
D:s
s03s
ceSs
lss
I}3s
Q3S
G03s
DA?E$
g?csos
9?0?1{
9?L024
gso1ts
93040?
980805
9sr112
CONCSNTRATIO
88
0. 100
0.300
0.137
0.0?{
l,ii.ii'.l{ax:mufti
lillo-..
*
,."
n
Case ID *
DATSS
961 02
CONCBNTRATIO
1
0.1C0
0. 500
0.214
0.168
GRTTES$
RESULT
0.200
0.200
Dis
0. ?00
Dis
ii.
Dis <
Dis <
Dis <
Dis <
300
0.200
t.
?00
0.200
0.200
I,NCO}ICENT
-2.303
-2 .303
-1.609
-1.204
*2.303
uq/l
UNITS$
ug./l
ug,/l
ug/l
ug/i
-2 .3C3 ugll
-?.303 ugll
-?.303 uqll
-2 " 303
-1.204
*2.0'i9
0.4?9
QTR COMPOUIJD$
(
Mercury,
Mercury,
Mercury,
Mercury,
Mercury,
25.000
26.000
28,000
29.000
30.000 l'{ercury,
981 r 1?
lil of cases
liq*nun
I{aximunr
Me6rr
-:$tandard Dev
Dis <
Dis <
LNCONCENT
24. C00
9? 0? 1.4
9?1 02 4
98 040 7
98 082 1
ffi
CAMPOUND$
Meleury,
Mercury.
Hercury,
Mercury,
Mercury,
Mercury,
Mercur:r.
Mercury,
22,000 Mercuxy, Dis
1
9?0505
6A{S
QTR
??.000
24.000
25.000
26.000
2?.000
26.000
29.000
30.000
961021
Dis
CP,TIESS
<
Dis
Dis
Dis
Dis <
Dis (
RSSUI?
0.200
0. 200
0. 500
0_40c
0.200
0.200
0.200
LNCONCENT
-2.303 usll
-?.303 ug/l
-0.693 us/l
-0.9J.6 ug,tI
-1.609 ug/l
-?.303 ug/1
-2.303 ug/l
UNITS$
LNCONCEN?
7
*4.303
-C. 693
-1.17
6
0.?tl
I
T=;;;;r**==--;;;;;-*==== .*;-=ffi;;il;;=--==xffi ;--=-=ffi ;;-T;ffi ffi ;*--=T;;;il====
C05S
961021
22,000
Mercury, Dis {
_2.303 ug,r1
0.200
g5S
I5S
I)5S
-€05$
605S
DsS
I5S
9?0505
9?0714
9^11024
980122
98040?
980805
9S1112
I
CONCENTRATIO
88
0" 100
0.100
0. 100
0.0
ti:*'*"."
$tarrdard
I
Dev
IIATE$
r Case ID T
GI
9610?1
-alr
Ii55'
rI)65.
E!6S
g065
S65
!}6s
I
3?0113
9?0?14
:
971021
980114
980406
98080{
981110
24.000
25,000
26.000
2?.000
28.000
<
<
Dis <
Dis <
Dl-s <
Dis <
Dis <
Mercury, Dis
Me.rcury, Dis
Mercury,
Mercury,
r{ercury,
29. 000 Mercury,
30.000 litercury,
ZCO
0.200
0"200
0.200
0.200
0. 2S0
0.200
0.
-2.303 u;/t.
_2.303 u;11
_?.303 Lr;/l
-2.303 ug/l
-2.303 u;/1
-Z . 303 ugl_l
-Z.3rE.n;/J-
I,NCONCENT
*2.303
-2.303
-2 .303
0.0
QTR
COMpOUND$ GP.TLES$
22.000 Mercury, Di.s <
23.000 Mercury, Dis <
grpretlr\r. ni e .
25..yyy
:-l ooo "-.*"Lx, ulr 25.000
!,!ercury, Dis <
2?.000 Mercury, Dis (
28.00C t4erclrry,
29. 000 Mercury,
30 " 000 Mercury.
Dis <
Dis <
Dis <
REST]I,T I,NCOI\:CENT
0.200
-2.303 uqll"
0.300
-2.303 u;/l
_2.303 us,/l
0.200
0.200
-Z "3W $A/I
0.200
-2.303 u;/i
0.200
-?.303 u;/1
200
0.200
0.
-2 . 303
-2 .303
u;/l
u;/t"
U}IIT5$
CONCE}ITRATlO
0. i00
0. 1s0
0.1c0
0.c
,tr,
TNCONCENT
sll
I
n
-2.303
ffi
*2. 30r
-?.303
0.0
w
i,t
ip;
f,;3
G0?$
9610?2
9?0:.13
9?0506
GS?S
9?0? 14
9?10?t
Iir
9801
1
4
980406
eQ?s
.&0?$
I
QrR
11.000
23,000
?4.000
25.000
?6.000
2?.000
28.000
29.000
30,000
98 082
I
981110
CONCENTRATIO
-l{ of
ca*es
l{!nirrum
0. 100
0.100
Iiiiil""."
*il"""o.
G0ss
DATES
9?0506
9?0?
1
{
COI'iCElitRAtIC
100
0.100
0. 100
nimum
0.
l{€ar:
ff;il:..*ml-*$1gS
951111
97C506
ill$S
li
hi
llaxil
?J1024
?!gl?3
980821
CONCSN?RA?IO
cases
0. 10c
muJlt
0.300
_,!lea*
tl " 140
0.089
*
til
6:.1S
*ii
DATN$
9?0?
1.
{
9?1024
98 01 15
98 04 03
980804
YUIILIY
COI{CENTPATIO
B
0.100
0.300
0.150
u:::::_:::""._
rn *
-*--
Mercuxy, D:'s <
Mercury, Dis <
Mercury, Dj_s (
0.200
0. ?00
-2.303
-2.303
*2.303
*?.303
ugll
ugll
ug/l
ug/l
Q?R CO!,IPOOND$
Mercury, Dis (
Mercury, Dis (
Mercury, Sis
Uercury, Dis
Melcuryf Dis
&lercury, Dis
GRTI,ES$
RESUL?
0.200
is;,!
uE/}
ug/t
lre
*2. 303 ug/l
n ?nn
<
<
<
0.200
0.200
<
0.200
0. ?00
LNCONCENT
-2.303 ug/l
-2.303 ug/1
?fi1
!.^/1
eYrr
-) krrvJ
*2.303 ugy'1
*2.303 uq/l
-?
ttrii
,
ir:
UNITS$
?n? ,!n./l
TNCONCENT
-2. 303
-2.303
-2.303
;*"*rilffi;;*-*ffiffi**Tffiil-*ffiffiffi--*-==ffi**
Mercury, Dis <
A00
"303
24,000
24. 000
26. 000
2?.000
29.000
<
<
<
Dis
Mercury, Dis
Mercury, Dis
Mercury, Dis
Mercurl.',
0.
.200
.200
0.200
0.300
0
0
*Z
ug,/1
_2.303 ug./1
*2. 303 ug/J.
_2.303 u;/1
-1.?04 uq,il
LNCONCENT
-2. 303
*1.204
*2.083
0.49I
QTR COMPOUND$ GRTTESS
Mercury,
Mercury,
M€rcury,
M€rcury,
Dis
<
Dis
Dis
nis
Mercuiy, Dis
Mercury, nis
Mercury, Dis
Mercury, D:.s
RSSUI?
0.200
0.300
0.200
0. 200
0.200
U.ZUU
0.200
0.200
TNCONCENT
-2.303 ug/]
-1 .204 ug/I
-1.609 u9,/1
*2.303 ug,/l
-1.609 ug/l
-2.303 ug,/]
!.JvJ
-?E. ?h?
rv'
UNITS9
qY/f
,,a/1
qYr 3
:,NCONCANT
I
*2.303
-1.204
-1. 992
__. .l"lll"____ _1":t_"
DATE$
961022
9?0506
9?0?14
9?1024
980115
980405
?99?94
car
r11
QTR coMPouND$ GRTtEs$
<
24 ,000 t{ercury, Dls <
25.000 l'tercury, Dis
27,000 Mercury, Dis <
28.000 l{ercury, Dis <
2e " 000 uercuf,y, Dis <
22.000 l,tercury, Dj$
Rgsutr LNcoNcENT
*2.303 ug/I
0.200
_2.303 u{/f
0. 200
0. 300
-1. A04 u;/1
0.20C
-2.303 u;/l
_?.303 u;ll
0.200
0.200
-2.303 u;/1
_2 . 303 u;/1
0. 200
0,?00
-2.303 u;/1
!t
t:;
I
-4. JUJ
'ln"
-,
22.000
24.000
?5.000
?6,000
??.000
28,000
29.000
30.000
9? 050 6
3 of cases
liniloLno
!{t&xl"mum
Fte{n
€fâa
-1?S
Il2$
VXzS
61?3
fiz$
I?!
rrrc
0. ?00
0. 200
ug,/I
UNITS$
5
mun
t Caae ID
0.200
0.200
0.200
0.200
ug/l
-2.303
*2.303
-2.303
-z,JuJ
LNi0NCSlit
22.000
24.000
25.000
26.000
??.000
28.000
961 022
of, cases
trt cf
l{ercury, Dis <
!{ercury, Dis <
Hercury, Dis (
ldercury, Dis <
i{ercuryr Dis <
I,NCONCEI.I?
0"0
98Cr2e
980403
lft
l}$
Elss
RESUI.T
d
0. 100
9? 102 t-
f;ii
SRTIES$
C0FIPOUNC,$
Mercury, Dis
uNrrss
ln
o,
CONCS:TRATXO
,8
""r**
0.100
0.3c0
0.1a5
0 .0?1
r*ale
3s-..'t,
rs i'
N
g
9
-e .303
J.
*1. ?04
'1
&
0.388
Q?*
nersg
{
I.NCONCENT
coHto$lE0$
?5.000 Hercury, Dis
9?A?1{
GRIIES$
<
RASELT
U. IUL
ITNCoNCSN?
*2.3C'3 ug./1
UNI?$$
cQHggil?RATI0 r-l{cstrcs$?
$*ffi'*
0.100
s.100
.l{ssrx
*riderd
0,t00
ic
:
a
iF
-3.3S3
*,.
$
jP!
JUJ
*?.3q3
s
j
0eY
w
r
:at *ai*.I*
s:4s
QTR
DATE$
coNc$lt?RAtro
,rl*nu*n
* l*lxufunum
s.1"00
0.100
4.1s0
GRfI,ES$
<
RESULT I,NCOHCSNT
C.200
-2.383 uglt
UI{ITSS
LltcoNcENr
t
I
.
CCtrtgoUNDg
45.000 Hercuryr Dis
9?s?x4
-?.3S3
"2.303
-e.303
*eas€&&gs****Ga$Be3s6tsE*Sq*E*e€***s*Fgsq=a*s&*E*as*&**eE&E*AE5sE_5sAeS
*!rf*'".
sii
Gl55
*95$
96111
I
2{,000 l,lercury,
25.000 ldersuryr
?S.00S HercBry,
27,000 Mercury,
28.000 Mercury,
?9.000 I'iercury,
3C,000 Hercury,
gAOq06
98{8?1
s81t 1r.
COHCSN1RATIO
$
s. 100
1.0s0
0.2$0
0.321
**
*
:
s*
t*
Dis
98080{
901111.
0.400
1.000
s-200
ois (
0. t00
0. 200
<
0.200
Dis
INCOHCE:{f
UNIIE$
"?.303 ug/1
-2.303 ug/l
-0.916 ug,/l
0.0
ug/l
-2.303 ug/l
-2,303 ugl!
-:.303 ugll
-2.303 ug/1
I
-2.393
0.0
*1.841
0"88S
25.000
?6.000
?1.000
28.000
?9.000
30.000
371030
9S0123
98S402
0. ?00
Dis <
Dis (
a*€ad*i5€gg*s€€s=e-=*aeEs5€es
CQ$'P0SNDS
e{"040 Her*ury, Dis
9?0?x{
RESUL?
0"200
Dis
Dis
2e.000 lgorcury, Di$
9?0508
6RTLSS$
<
<
LNCONCEN?
Q?R
DATE9
9S1 1L 2
xffi
$1$.s
CAHPOUiIDS
22,000 t{ercury. Dis
9*$r*3
liel**"n**
* qase IP
Q?R
b*?s$
9?0$0?
9?0?14
9?1020
tka:."
$ffin*"*
GRTLES$
RESIJL? TNCONCENT
*2.303 ug/l
0.200
0.?00
-?,303 us/]
0,20S
-2.303 ug./t
1,100
0.095 us/l
0.20S
-2"303 ugll
*0"693
0.500
us/l
0.?00
-2,3$3 ug/l
0"200
-2.303 6gll
GRILES9
RE$iJtT I,NCO$CENT
0-?00
-2.303 uq/l
0.?00
-?.303 usll
$.200
-2.303 ug/t
S.500
-0.693 uq/l
0. 200
-2.303 u9/1
*2.303 uq/t
0.200
0"200
-2.303 ug/l
0.200
-2.303 uq/}
<
<
l{ercuty, pis {
blercury, ois
M€rcury, Dis <
llercury, Dis
Mereury, Dis <
lrtercury, Dis (
UNT1S$
coNcsNTRAtI0 t$coNcsNl
0.100
1 l nal
!{axinum
t{e4r:
[ri
x1?$
61?$
lr?9
I[?$
!r7s
-J
c*se*
I$'bf,
0.2?5
0.36?
gArE$
0. 095
*:..80?
0"951
QTR
sEs*E*s&4*Es=€a!
COldpouNDS
2t,000 Hercury, Dis (
95111?
9?0509
Mercury. Dis
Mercury, Dis
<
30.000 Mercury, Dl.s
<
24,000
25"000
26.000
??-000
1S.000
gzoiis
<
uercury, Dis
tlercury, Dis (
Mercury. Die <
?9.0C0 !{ercury, Ois <
9?10?0
98*!1i
s80d0?
9808Sd
98111l
ry;:ilH
'ua*rr
J:::
I
I
],#.ii'"'
* g&Eq Is r
jgl?$
r1 ?s
.l
iaa
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li

frtr - Peoria County

Transcription

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