Document Q7qm08aoJGB9bq0mnJjzQ2B8
EPA VINYL CHLORIDE STANDARD -- 1980 EPA VINYL CHLORIDE STANDARD - 1980
EPA VINYL CHLORIDE STANDARD
O
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051409
19 to
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051410
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ucc 051411
variable ad
MUMf NTS
N
MEAN
STD OEV
SKEVNESS SS cv
TIMEANsO 01 NORMAL
Sc5 11.991 47.1966
9.17263 1242708
393.6 5.82137 9.20867
SUM 0T S SUM VARIANCE KUHTOS1S CSS STU MEAN PROB>1T1 PR0B>0
BAR CHART 600*.
5TATIS11CAL ANALYSIS univariate
system
13(45 MONDAY UtCtMBEM 22. 1980' 1
525 6295.29 2227.52 101.738 1167221 2.05983
0.0001 0.0001
(JUAN I ILtS
100% MAX 754 03 50k MED 25k Q1 Ok MIN __
RANUE 03-01 MODE
611.95 6.6425
2.03 0,4525
0
611.95 6.39 o.i
Vd* SfU* iu*
1*
# BOAPLOT
600*
178.582 36.9996
16.03 0.13 0.1
0.0849999
tAlHtMtS
LOWEST .0
0.0J 0.0 3 0.03 0.08
HI lintsi 181.66 208.45 368.2 596.6/ 611.95
NUHMAL PROBABILITY plot
c
I*
J> 5 f
e
300
I JL 5 6 sna_*-
300
MAY REPRESENT UP TO 10 COUNTS
-2 -l
18
7
f> 1 n
VALUE COUNT 01
* 10
' 42 13 !
" .\
B?
0.03 0.08
0.1 0.11
0.12 0.13 0.14
0.15 0.17
3 1 42
2 2 5 3 3 1
'1 -*V. |
C*
0.18 0.19
0.2
2
1 3
iL_1
--1 g, a
^ cs c ui o
L ^
wA 3R >
0.22 0.23 0.24 0.25 0.26
2 4 4
2 3
0.27
5
-6.28
3
0.29
6
PEPCtNTS CELL CUM
0.2 0.2 0.6 0.8 0.2 1.0 8.0 9.0 0.4 9.3 O.A 9.7 1.0 10.7 0.6 11.2 0.6 11.8 0.2 12.0 0.4 12.4 0.2 12.6 0.6 13.1 0.4 13.5 0.8 14.3 0.6 15.0 0.4 15.4
0.6 16.0
1.0 17.0 0.6 17.5
,1.0 18.5
FREQUENCY TABLE
PERCENTS
VALUE COUNT CELL {CUM
0.3 3 0.6 19.0
0.31
1 0.2 19.2
0.32
2 0.4 19.6
0.33
3 0.6 20.2
0.34 . 4.
_ 2UU.
0.35
3 0.6 21.5
0.37
1 0.2 21.7
0.38
3 0.6 .22*3
0.39
1 0.2 22.5
0.4
1 0.2 22.7
0.41 -JL, --0,4___2A.1L.
0.42
1 0.2 23.2
0.43
2 0.4 23.6
0.44
4 0.8 24.4
0.45
3 U.6 25.0
0.46
1 0.2 25.1
0.41
.1 . .0*2 . .25.3
0.48
1 , 0.2 25.5
" J A49 . 0 .5.1
1 0.2 25.7 - 0*6- 26.3
0.52
3 0.6 26.9
VALUE COUNT
(1.55
1
0.56
3
(1.57
1
0.58
2
.0.59
1
0.6
1
0.63
1
0.64
4
0.65
3
0.66
1
0.67
1
0.68
1
0.69 0.7
0.71
-1 2
3
0.73
2
0.74
1
0.75
3
0.T8
2
-*-1
0.83
2
PERCENTS
CELL CUH 0.2 27.0 0.6 27.6 0.2 27.8 0.4 28.2 0.2 28. 4
0.2 28.6 0.2 28.8 0.8 29.5
0.6 30.1 0.2 30.3 0.2 -30.5
0.2 30.7 0.2 30.9 0.4 31.2 0.6 31.8 0.4 32.2 0.2 32.4 0.6 33.0 0.4 -J3.3 --0.2 'TSr.S 0.4 33.9
0 1 *2
PtRCtNlS
VALUE COUNT CtLL CUM
0.84
1 0.2 3a. 1
0.86
1 0.2 34.3
0.87
1 0.2 34.5
0.88
1 0.2 34.7
0.91
2 0.4 35.0
0.92
1 0.2 35.2
0.95
1 0.2 35.4
0.95
2 0.4 35,8
0.97 0.98
2 0.4 36.2 1 0.2 36.4
1 1 0.2 36.6
1.01
2 0.4 37.0
1.02
1 0.2 37.1
1.04
1 0.2 37.3
1.06
1 0.2 31.5
1.1 1.11
2 0.4 37.9 1 0.2 38.1
1.15 1.18
* A*afe6> 38.71 0.2 3b.9
1.2 1 -0-2 39.0
1.22
2 0.4 39.4
>
y
y
y
y
y y y o ) y
o 3
w
STATISTICAL ANALYSIS STSTErt
13J45 MONDAY. DtCEMbtK 22i 1980
UNIVARIATE
VARIABLE AD
frequency Table ilont.i
PERCENTS
PERCENTS
PERCENTS
PEMCtNTS
VALUE COUNT CELL CUN
VALUE COUNT CELL CUM
VALUE count CELL CUM
VALUE CUUN1 CELL CUN
I.25
1 0.2 39.6
2.27
1 0.2 52.8
3.T 1 0.2 63.4
bm Ttt
1 0.2 /*;>
1.29
3 V.b 40.2
2.26
1 0.2 63.0
3.73
1 U.? 63.6
6./7
1 0.2 (4.7
t:
1.31
3U
40.8
2.32
1 0.2 53.1
3.T6
1 0.2 63,8
o.t)2
1 0.2 f 4,9
1.35
d 0.4 41.1
2.33
1 0.2 63.3
3.89
2 0.4 b4.2
b.ttb
1 0.2 75.0
1.36
1 0.2 41.3
2.36
1 0.2 53.5
3.93
1 0.2 6**4
o*ttV
1 0.2 15.2
1.3T
1 0.2 41.6
2.37
2 0.4 53.V
3.95
1 0.2 64.6
6,9 1 0.2 75.4
1.38
2 0.4 41.9
2.4
1 0.2 54.1
3.97
1 0.2 64.8
6.91
1 0.2 75.6
1.4 2 0.4 42.3
2.41
1 0.2 54.3
4.06
d 0.4 65,1
'.01
1 0.2 f 6 . B
<9
1.AI
1 0.2 42.5
2.43
1 0.2 54.5
4.07
i 0.2 65.3
1 .is
d 0,4 7b,
1.43
1 0.2 42.7
2.45
. 2 0.4 54.i_________ 4.09
i 0.2 65.5
'.If
1 0.2 10 *4
1.45
1 0.2 42.9
2.51
1 0.2 55.0
4.11
i 0.2 65.7
7 .22
1 0.2 76.6
9
1.46
d
43.2
2.52
1 0.2 55.2
4.19
i 0.2 65.9
7 .27
d 0.4 77.0
1.49
i 0.2 43.4
2.54
l 0.2 55.4
4.2
i 0.2 66.1
7 .31
i 0.2 77.1
1.5 i 0.2 43.6
2.62
l 0.2 55.6
4.21
i 0.2 66.3
f.45
i 0.2 7 7.3
1.52
i 0.2 43.6
2.66
1 0.2 55.8
4.24
i 0.2 66.5
f .48
i 0.2 77.5
1.58
3 U.6 44.4
2.69
1 0.2 56.(L_________ ____4.3
i 0,2 66.7
f .59
i 0.2 77.7
1.63
1 0.2 44.6
2.7
2 0.4 56.4
4.33
i 0.2 66.9
7,61
i 0.2 77.9
1.65
1 0.2 44.8
2.71
1 0.2 56.6
4.36
i 0.2 67.0
7.66
i 0.2 78.1
1.66
1 0.2 45.0
2.74
1 0.2 56.8
4.3#
i 0.2 67.2
f .68
i 0.2 78.3
1.69
1 0.2 45.1
2.6
1 0.2 57.0
4.48
2 0.4 67.6
f.8T
i 0.2 7h.5
1.73
d 0.4 45.5
2.81
1 0.2 57.1
4.49
2 0.4 68.0
7 .88
i 0.2 78. 7
1.75
i 0.2 45.7
2.65
1 0.2 _-57.2_________ __ 4.53
1 0.2 68.2
/ .93
i 0.2 78.9
1.76
i 0.2 45.9
2.86
1 0.2 57.5
M
2 0.4 68.6
7,96
i 0.2 79.0
1.77
i 0.2 46.1
2.87
1 0.2 57.7
4.8
1 0.2 68.8
8.01
t 0.2 79.2
1.78
i 0.2 46.3
2.89
l 0.2 57.2...............
0.9
1 0.2 69.0
8.09
i 0.2 79.4
1.79
2 0.4 46.7
2.93
1 0.2 58.1
4.97
2 0.4 69.3
i 0.2 79.6
1.8 1 0.2 46.9
2.96
1 0.2 58.3
4.99
i 0.2 69.5
8.38
i 0.2 79.8
1.61
1 0.2 47.0
2.99
l - iU2.~ 58.5-------------- 5.02
i 0.2 69.7
6.4
i 0.2 80.0
1.63
1 O.P 47.2
3 1 0.2 58.7
5.17
i 0.2 69,9
8.43
i 0.2 80.2
1.84
1 0.2 47.4
3.02
1 0.2 58.9
5.33
i 0.2 T0.1
3*4t)
i 0.2 80.4
1.66
1 0.2 47.6
3.09
1 0.2 59.0 -------- 5.44
i 0.2 70.3
8.5
i 0.2 80.6
1.69
2 0.4 48.0
3.12
1 0.2 59.2
5.51
i 0.2 70.5
8.57
i 0.2 ttU.tf
1.91
1 0.2 48.2
3.13
1 0.2 59.4
5.57
i 0.2 70.7
6.58
i 0.2 81.0
1.92
1 0.2 48.4
a.i*
1 _1U2_-59.6__
___ 5,58 ____ i _ 0.2- 70.9
6.6
i 0.2 61.1
1.93
2 0.4 48.8
3.19
1 0.2 59.8
5.62
i 0.2 71.0
6.73
i 0,2 81.3
1.94
2 0.4 49.1
3.23
1 0.2 60.0
5.63
i 0.2 71.2
8.79
i 0.2 81.5
1.95
1 0.2 49.3
3.25
-- L- 8.2- 60.2
------- - 5.68
i 0.2 71.4
8.9
i 0.2 81.7
1.99 2.02 2.03 2.04
1 0.2 49.5 1 0.2 49.7 3 0.6 50.3 1 0.2 50.5
*
3.26 3.27 3.28 3.31
1 0.2 60.4 1 0.2 60.6 -i_ __IU2-,-6IU8-----------1 0.2 61.0
5.74 5.79 5,85 5.88
i 0.2 T1.6 i 0.2 71.8 i 0.2 72.0 i 0.2 72.2
9.02
y.uti 9.13 9.42
i 0.2 81.V i 0.2 82.1 i 0.2 02.3 i 0.2 82.5
ucc J4A
2.07 2.09
2.11
2.12 2.16
1 0.2 50.7 1 0.2 50.9 1 0.2 51.0 2 0.4 51.4 2 0.4 51.6
3.34
1 0.2 61.1
5.97
3.36
1 - -0.2 - 61.2 . .......- 6.12
3.46
1 0.2 61.5
6.23
3.49
1 0.2 61.7
6.33
2.51 ---------1_ --IL.2___61.9----------- --6.42
2 0.4 72.6 1 0.2 72.8 1 0.2 73.0 1 0.2 73.1 1 0.2 73.3
9.47 9.5
9,59
9. f 3 9.91
i 0.2 82.7 i 0.2 82.9 2 0.4 83.2
1 0.2 8J. 4 1 0.2 83.6
. 2.19
1 0.2 52.0
3.52
3 0.6 62.5
6.44
2 0.4 73.7
10.U2
1 0.2 83.8
f 2.2
2.21
2.22
1 0.2 52.2 1 0.2 52.4
1 0.2 52.6
3.57
2 0,4' 62.9
_____sute- <T*. ..4--- -JU2-63.0__________-
3.69
1 0.2 63.2
6.49 6,6* .
6.75
1 0.2 73.9 . L -0,2- iAj______
1 0.2 74.3
10.07
1
ID.21 _____1
10.28
1
0.2 ' 64.0 -0*2 --*6,2-
0.2 84.4
JX1*
9
1
9
9 9
*
J
9
9
l 9t
VARIABLE AD
9 ft ' 7--
9 2
h3
9
14 '>
10
9
17 l
14
9
10 ?'
f3
9
Z (*
i*
t (7
!
te
VALUE COUNT
10. T6
1
11.02
1
11.6
2
11.67 11.68
.1
1
11.66
1
12.1
1
12.AT 12.6S
1
l
12.7
1
13.28 13. AT
1
l
1A.09
1A . 13
1 1
1A . 35 1A . A
1A.A9
1
1 1
15.71
1
16.01
1
16.26
1
16.61
1
PERCENTS CELL CUM
0.2 6A.6 0.2 8A.0
0 . A 85.1
0.2 65,3 0.2 85.5
0.2 65.7 0.2 85.9 U.2 86.1 0.2 86.3
0.2 86.5 0.2 86.7 0.2 86.9 0.2 87.0 0.2 87.2
0.2 87. A 0.2 87.6 0.2 87.8 0.2 88.0 0.2 88.2 0.2 80.A 0.2 88.6
STATISTICAL analysis UNIVARIATE
SYSTEM
13iA5 MONDAYt DECEMBtH 22.
ENEUUENCY TABLE tCONT .
PERCENTS
VALUE COUNT CELL CUM
16.72
1 0.2 88.6
17.1a
1 0.2 89.0
17.15
1 0.2 89.1
17.62
1 0.2 89.3.
17.50
1 0.2 89.5
17.97
1 0.2 89.7
10 1 0.2 89.9
18.06
1 0.2 90.1
18.1A
1 0.2 90.3
10.A
1 . 0.2 90.5 - - _
18.58
1 0.2 90.7
18.66
1 0.2 90,9
18.8
1 0.2 91.0
19.3
1 0.2 91.2
19.37
1 0.2 91.A
20.5A
1 0.2 9L.6__ ______
20.76
1 0.2 91.0
22.A
1 0.2 92.0
23.56
1 0.2 92.2
23.7
1 0.2 92.A
2A.71
1 0.2 92.6
value COUNT
25. A1
1
26.06
1
26.95
1
27.33
1
30.33
1
30.07
1
31.61
1
31.71
1
32.52
1
3A.6
1
37.36
1
37.86
1
39.38
1
AO.56
A1.6A
1 1
A3.73
1
AA.A2
1
A9.26 52.84
1
1
5A.93
1
58.61
1
PERCENTS
CELL CUM 0.2 92.8
0.2 93.0
0.2 93.1
0.2 93.3 0.2 93.5 0.2 93.7 0.2 93.9 0.2 9A.1 0.2 9A.3 0.2 VA.5 0.2 VA.T 0.2 9A .9 0.2 95.0 0.2 95.2 0.2 95. A
0.2 95.6 0.2 95.8 0.2 96.0 0.2 96.2 0.2 96. A 0.2 96.6
VhLUE COUNT
60.02
1
7 3.9
1
101.Ob
1
11A.73
1
1i6.7 A
1
110.33
1
13a.67
1
1A 7.27
1
167.13
1
160.35
1
173.59
1
170.05
1
170.76
1
181.66
1
200.A5
1
360.2
1
590.67
1
611.95
1
PERCtNIS CELL CUM
0.2 96.0
0.2 97.0 0.2 97.1 0.2 97.3
0.2 97.5 0.2 97.7 0.2 97.9 0.2 90.1 0.2 98.3
0.2 90.5 0.2 90.7 0.2 90.9 0.2 99.0 0.2 99.2 0.2 99. A 0.2 99.b
0.2 99.8
0.2 100.0
9
w w
9 4
L
statistical
ANALYSIS
SYSTEM
lj!46 .UNUYi UtetMbLM 22. I960
4
UNIVARIATE
VARIABLE LNAO
MUM^nTS
N MEAN STD DEV SKEWNESS SS CV T 1 MEAN0
01 NORMAL
5(14
0.653211 1.0424
0.220457 1998.87 282.052 8.11589
1.0/456
SUM WGTS SUM
VARIANCE KURTOSIS CSS STO MEAN PRQH>1T|
PROH>D
524
342.283 3.39443 -0.181395 1775.29 0.0804655
0.0001 0.19864b
gUANlILES
100* MAX 6.41665
76* U3
1.92425
50* MED 0.708036 25* Q1 -0.776529
0* MIN -3.50656
___
RANGE 03-01 MODE
9.92321 2.70078 - -2.30258
SI SI*
95* 90* 1U*
t3* 1*
5.18509 3.66536 2.8923/ -2.04022 -2.30258 -2.30258
txTHcMtS
LOWEST -3.50656 -3.50656 -3.50656 -2.52573
-2.30258
HlGHtST 5.20214
5.339/ 5.90863 6.39136
6.41665
BAR CHART h+**
*
_ ttftftftftftftftftftftft
***********
MISSING VALUE . ________ COUNT
* COUNT/NOBS
1 0. 19
U U
U *
, ttftft
-4 ------- +--------.--y
may represent up TO 1 COUNTS
-.
_.
\
* 2 1 a 5
12 14 33 4T 49 58 61 , 34 45 J4 42 16 54
1
_____ A. ..... .
BOAPLOT
ft
u 0 11 |
1 1 1 1
11 11 ft --ft--*
11 tt ------ft
1 l 1 ( 0
WAR IABLE LNAD
STaTISIICAL ANALYSIS
univariate
SYSTEM
131*5 tiONIJAYi UELtHBEH 22* 198^H 5
NORMAL PROBABILITY PLOl 6+
2.5*
***
***
***
*4
4
VALUE COUNT
-3.50656
3
-2.52573
1
-2.302bB
*2
-2.20727
2
-2.12026
2
-2.0*022 -1.9*611
5 3
-1.69712
3
-1.77196
1
-1.71*8
2
-1.66073
1
-1.609**
3
-1.51*13
2
-1.*6966
*
-1 .*2712
*
-1.38629
2
-1.3*707
3
-1.30933
-1.27297 -1-237H7
5 3 5
i -1.20397
3
-1.1711B
1
|__ 9*4*139*3
2
-1.10866
3
CELL
0.2 ti.o 0.*
1.0 U .6 0.6 0.2 0.* 0 .2 0.6 0.4 U.H 0.8 0.* 0.6 1.0 0.6 1.0 0.6 0.2 0.* 0.6
CUM 0.6 O.U 8.8 9.2 9.5 10.5
11.1 11.6 11.8 12.2 12.* 13.0 13.*
l*.l 1* .9
15.3 15.8 16.8
17.* 18.3 18.9 19.1 19.5 20.0
-0.5
***** *******
.***#+ JtfftIL--- -----
*******
-4*
-2 -1
1 2
EREQUEI6f TABLE
PERCENTS
VALUE COUNT
-1.07681
*
-1.0*982
3
-.99*252
1
-.96758*
3
-.9*1608
1
-.916291
1
CtLL 0.8
JU6 0.2 0.6 0.2 0.2
CUM
VALUE COUNT
20.8
-.4*6281
*
21.* - ____ -*430783 -
3.
21.6
- *p.415S15
1
22.1
6.400478
1
22.3
-a. 385662
1
22.5
-.371064
1
CELL CUM 0.8 29.4
-0.6 JO.O 0.2 30.2 0.2 30.3
0.2 . 38.3 0.2 30.7
-.891598
2 0.4 22.9
-.356675
2 0.4 31.1
-.867501
1 0.2___23.1 ___ - -0*342*9- - 3 ...0.6--31.1 --
-0.84397
2
-.820981
*
-.798508
3
-,77b529
1
-.755023
1
-.733969 . L
-0.71335
1
-.6733*5
3
-.653926
3
-.597837
1
-.579818
3
-.562119-______ l-
-.5**727
2
-.527633 . 1
-- * 9-1MBCO ' . *--
-.462035
1
0.6 23.5
' -.314711
2
0.8 20.2
>.901105
0.6 24.8 . 1 -.287682
1 3
0.2 25.0
-.248*61
2
0.2 25.2
-.2231*4
1
0*2- - 25.4- __ ,=*18633
2.
0.2 25.6
>*.17*353
1
0.6 26.1
-.150823
1
0.6 26.7
--.139262 . 1
0.2 26.9
-.127833
1
0.6 27.5
-.09*311
2
27.7 -_-^-Jj*I1B3J82.
1
0.4 28,1
-.072571
1
0.2 28.2
-.051293
2
______ **030659__ .. _2-
0.2 28.6
-.020203
1
0.4 92.1 0.2 32.9 0.6 32.8 0.4 33.2
0.2 33.4
0*6- .33.8___ 0.2 34.0 0.2 34.2 0.2 34.4 0.2 34.5 0.4 34.9 0. 35.1 0.2 35.3 0.4 35.7 u.*r 36.1 .
0.2 36.3
v*Lue COUNT
01
.0099503
2
.0198026
i
.0392207
i
.0582689
i
.0953102
2
0.10*36
1
0.139762
3
0.16551*
L
0,182322
i
0.198851
2
0.2231*4
i
0.25*6*2
3
0.270027
3
0.300105
2
0.30(485
l
0.31*811
i
0.322083
2
0.336*72
2
0.3*359
i
O.357o7*
t
0.37156*
1
. 0.378*36
2
0.398776
1
PtHCENTo
CELL Cum
U2 3b. 5
0.4 Jb. 8
0*2 37.0
0.2 Si .2
0*2 31*4
0.4 37 .8
V.2 3b. 0
U.b 38.5
0.2 38.7
0.2 38.9
0 .4 39.3
0.2 39.5
0.6 *0.1
0.6 *U*b
0.4
0.2 0*2 U.4
*1.0 41 .2 41*4 41 * b
0.* 42*2 0.2 42*4
0.2 ^ 42 *b
0 *2 42*1
-0.4 4 3 1
0.2 43*3
a *
*1 *
ucc
051417
variable lnad
value COUNT
0.408465
1
0.41071
1
0.467426
3
0.48886
1
0.S0077S
1
0.806818
1
0.524728
1
0.848121
2
0.559616
1
U.868314
1
0.87098
1
0.876613
1
0.562216
2
0.887787
1
0.593327
1
0.604316
1
0.609766
1
0.620576
1
0.636577
2
0.647103
1
0.652325
1
0.65752
2
0.662688
2
0.667829
1
0.688135
1
0.703097
1
0.708036
3
0.71295
1
0.727549
1
0.737164
1
0.746668
1
0.75141b
2
0.770106
2
__ 0.763902
1
0.788457
1
0.192992
1
-- 0.797507
1
0.81978
1
0.824175
1
0.841567
l 0.845868
1 1
1* 0.658662
1
,,___ 0.86289
2
0.875469
1
0.879627
1
------- 0*887891
1
%*896088
2
$? <1920263
1
ln<--8*924259
1
0.9321*4
1
CELl 0.2 0.? 0.A
0.2
0.2 0.2 0.2 0.4 0.2 0.2 0.2 0.2 0.4 0.2 0.2 0.2 0.2 0.2 0.4 0.2 U2 0.4
0.4 0.2 0.2 0.2 0.6
0.2 0.2 0.2 0.2 0.4 0.4 0.2
0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.4
0.2 0.2 0.2 0.4 0.2 0.2 0.'
CUN 43.5 43.7 44.3 44.5 44.7 44.8
45.0 45.4 45.6 45.8 46.0 46.2 46.6 46.6 46.9 47.1
AT.3 A 7,5 A7.9 A8.1
A6.3 A8.7
A9.0 A9.2
A9.4 49.6 50.2 50.4 50.6 50.8 51.0 51.3 61.7 51.9 52.1 52.3 52.5 52.7 52.9 53.1
53.2 53.4 53.8 54.0 54.2
54.4 54.6
55.0 55,2. 55.3
S 7 a T ISTICAL ANALYSIS UnWIRIATE
S YS T E N
13!45 SUNDAYt OtCEHBEN 22, 1980
EHEUUENCY TABLE (CONT.)
PERCENTS
PERCENTS
VALUE COUNT CELL CUN
VALUE count CELL CUM
VALUE COUNT
0.963174
1 0.2 55.5
1.43746
i 0.2 66*2
2.00621
1
0.985817
1 U.2 56.7
1.44456
i 0.2 66.4
2.61223
1
0.989541
i U , 2 55.9
1.45861
l 0.2 66.6
2.02663
1
0.993252
2 0.4 56.3 ..______ 1*46557
i 0.2 66.6
2.02946
1
0.996949
1 0.2 56.5
1.47247
i 0.2 67.0
2.03601
1
1.00 796 1.02962
1 0.2 56.7 1 0.2 56.9
1.47476 -1.49962
i 0.2 67.2
0.4 67.6
2,03662 2.06306
1 1
1.03316 1.04732 1.05082
1 o.2 57.1
1.50185
1
57.3
1.510/2
1- 0.2 - 57.4 - ______1*52606
2 0.4 67.9
1 0.2 68.1
U .4 68.5
2.06433 2.0/066 2.01443
1 1 1
1.05431
1 0.2 57,6
1.56862
i 0.2 68.7
2.06U69
1
1.06126
1 0.2 57.8
1.58923
i 0.2 68.9
2 090b3
1
1.075
1 0.8 -58.[L _ ______ 1*60342
2 0.4 69.3
2.1234b
1
1.08519
1 0.2 58.2
1.60744
1 0.2 69.5
2.1*585
1
1.09527
1 0.2 58.4
1.61343
1 0.2 69.7
2.12623
1
1.09861 - 1 -JUii. - 58*6___ __1.64267
l 0.2 69.8
2.1316
1
1.10526
1 0.2 $8.8
1.67335
1 0.2 70.0
2.13/71
1
1.12817 1.13783
__ Li.) 0.2 59.0
1 0*2. 59*2--
;1.69378 70656
1 0.2 70.2 1 0.2 70.4
2.14007 2.1462/
1 1
1.14103
1 0.2 59.4
1.71739
1 0.2 70.6
2.14443
1
1.15057
1 0.2 59.5
1.71919
1 0.2 70.8
2.161/6
1
1.16002
1 - 0*2_. 59*7__ ____ 1.12633
1- --0.2- 11.6--
2.1667/
1
1.17246 1.17865 1.18173
1 0.2 59.9
1 0.2 60.1 1 - 0*2. 60.3--
i >1**7mi2T*Uti
1 0.2 71.2 1 0.2 71.4
l 0.2- 11.6
2.11361 2.1660S 2.19444
1 1 1
1.18479
1 0.2 60.5
1.75613
1 0.2 71.8
2.2060/
1
1.18784
1 0.2 60.7
1.76644
1 0.2 T1.9
2.211b/
1
1.19695-- - 1. U.2_ -60*9----
,.1.71156
1-- - _____0*2 ---72.1 _
2.24264
1
1.20597
0.2 61.1
1.76679
2.24613
1
1.211VA 1.24703
0.2 61.3 0.2 61.4
1.61186 1.62936
2.26129 2.260/2
1 2
1.2499
0.2 61.6
1.6463
2.2/621
1
1.25562
0.2 61.6
1.66942
2.29364
1
1.25846
253
2.30466
1
1.2T2S6 1.28447
67026 .69311
2.30966 2.3233/
1 1
1.30563
2.3302
1
130833 1.31441
3.3213 1.3SS41
1.91102
1.9125
-,.,,.1*91986mu 2$
1 0.2 74.4 1 0.2 74.6
1---0.2- 24.8-------1 0.2 75.0
2.3/564 2.399/1
2.451 2.45/02
1 1 2
1
1.36664 1.37372
; *4*93607 -bia* 93152
1 0.2 75.2 1 0.2 75.4
2.45/682.4731/
1 1
1,37877
1.93297
1 0.2 75.6
2.49321
1
1.40116
1.94734
1 0.2 75.8
2.52332
1
1.40364-
-**-1.96711
2 0.4 76.1
_ 2.53/66
1
1.49684 1.41342
l
\
M 1.9699 -* 1.97685
1 0.2 76.3 1 0.2 76.5
2.5416 2.56626
1 1
1.43211 Jtfirl.
AM. 98376__ . - 2 .9*6-.26*9___-
-2.60046
1
1.43508
66.0
1.98924
1 0.2 77.1
2.6*546
1
PtRCLNTs
CtLL CUN 0.2 7 7.3 0.2 ' 1/.5 0.2 77.7 0.2 T/.9 0.2 Tu.l 0.2 f 8.2 0.2 18.4 0.2 76.6
0.2 Iti.tj
0.2 19.a 0.2 19.2 0.2 79.4 0.2 19.6 0.2 79.8 0.2 80. U 0.2 80.2 0.2 80.3 0.2 60.5 0.2 8U.T 0.2 60.9 u .2 61.1
U.2 61.3 0.2 81.5 0.2 61.7 0.2 61.9 0.2 82.1 0.2 62.3 0.2 62.4 0.2 82.6 0.2 62.6 0.4 83.2 0.2 63.4 0.2 63.6 0.2 63.8 0.2 64.0 0.2 64.2 0.2 64.4 0.2 64.5 0.2 84.1 U..4 65.1 0.2 65.3 0.2 65.5 0.2 65.7 0.2 65.9 0.2 bb.l 0.2 86.3
0.2 86.5 0.2 86.6 0*2 -.66*6 0.2 81,0
M
I*
*S|
TV
---- VARIABCE-OUO------
value COUNT
2.8483
1
2.66375
1
2.66723
1
2.673*6
1
2.7543
1
2.77321 2,1099*-
1 1
2.01
1
2.81661
1
2.6*1*1
1
2.8*2
1
2,8633*
1
2.88876
1
2.8887
1
2.89037
1
2.8937
1
2.89812
1
PERCENTS CELL CUM
0.2 87,2 0.2 87.* 0.2 87.6
0.2 87,8
0.2 88.0 0.2 88.2 0.2 88.*
0.2 88.5 0.2 88.7 0.? 88.9 0.2 89.1
0.2 89.3 0.2 89.5 0.2 89.7 0.2 89.9 0.2 90.1 0.2 90.3
mm.
mmm
STAT 1
mw?*
51S SVSTEM
I3i*3 MUNUAK, UECEHbtR 22*
FHEUUENCV TABLE (CUNT.)
VALUE COUNT
2, mod 2.9203#
2,93386
2.9601 2.9*373 3.02237 3.03303 3.10906 3.15965 3.165*7 3.20721 3.2151*-___
3.260* 3.29390 3.30790 3.4121*
PERCENTS CELL CM*
0.2 90.6 0.2 90.6 0.2 91.0 0.2 91,2
0.2 91.4
0.2 91.e 0.2 92.0 U.2 92.20.2 92,* 0.2 92.6
0.2 92.9 0.2 93.1 0,2 93.3---
'* :
A value
3.*6327 3.*6663 3.66106 3.6*366 i 3.6206 .3.63389 3.o7326 3.70276 2.73366 1 3,77603 i 3,79369
11 3.96727 4,00606
*.0709 4,10792
COUNT 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
PERCENTS CELL CUM
U.2 - 93.7 U.2 93.9 0.2 9*.1
U.2 96.3 0.2 96.6
0.2 9*.7 0.2 94.6 0.2 9S.0 0.2 98.2 0.2 96.6 0.2 96.6 0.2 96,6
0.2 96.0 U.2 96.2 0.2 96.* 0.2 90.6 0.2 96.6
VhLUt COUNT
*.302(1
1
4.013/1
1
*. 7*c3rt
1
4.73993
1
*, 7/34a
1
*,90^83
1
*.9922/ 5.110(1
1 1
3.18O0*
1
3.160/
1
5.16*06
1
5,leuo*
1
5.2021*
1
3.339/
1
6.90663
1
6.39136
1
6.*1063
1
PtRCLNl3 CLLL Co*
U* vo.v O.ti W.l
u.t? *t. J U. W.3
O.t
\i.<t
U.4
o.tt
v/. t
V (* V *#0.1
v4 J
i)*d iA.it
0 .it
st.it
*#0.5 VO. f Vt>9 V vv*o
ii.C
ti.it IJ.it
Vv.o
Si.it w.tt
si.it 4 U U . U
1-.........
ucc
051416
74'.
7$Cff
770 S'. C/MFS
>fd ^ /ffc
if.
S7%psr?c*t fvu&tJHiti/ <7^ 7/a>y<l Mot/ae 2AP9- &(t sa/e+r i/wvi. fS/jus snt/ffs#( - &ja/7/*#4Y s>* *i/Mr/rs Mfryf/f
J/m :
/+ 7/*0feT?0AJ */7P 004 AS/iAC 7* fS4 &/ ff&tr
f&M 7fl A*#ypf42 MS7XSC?U4fS /A/ r#i MfSMfAS /UGo240t/+j
/r /'0&,0 4sss/&y ii A-
70 (fir 7#f** fftrM/G
00($'0*7'At /A/40604/97/0+) /P +f 40470 /+ 70t 47744H)
0474 iy y/#z /0<f-(us***- A/ii/rcM.
/ h/tlC fi **/ 7ACS-7794/ 9a/7/+
4/i0 7i44 S
so y/y Af#y sc/rewct /7~ at yj*4 T^A/yi+os+rf^ 00/0
of rMJtsf;
*-rpy a 74***??a ys* at~ yf*c's 7*0.
T/yArtfs &* 44y #&> yjy 6*v G/t/e *
AG4//0 - 4m7*v* Sir 7P /K/#r-#/rs awu/Mt mr <**xe
/ Mya/ 7#$ {(2 #rys 7y9 pr00/00S2y 4/0 + rAtsi G Afitt)
iwm if
Goer.
+72 y
7fr
#90/0--
Ucc
OSHig
INTERNAL correspondence
TO: J. F. Erdmann Texas City Plant
cc: S. A. Dickerson J. B. Leverton D. G. Reese G. F. Tacquard G. E. Vaughan
UC 149-- t
P. o. BOX 471, TEXAS ClTV. TEXAS 77S
Date: December 10, 1980 Subject: Semi-Annual EPA Report
Attached are the summary values of residual vinyl chloride In UCAR Solution Vinyls stripped varnish. The data Includes the period from March 1 through August 31, 1980. This should satisfy your requirements for the Semi-Annual EPA Report.
Sincerely,
P. D. Smith
PDS/st Attachments
UCC 051420
Date
1
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
22
23 24 25 26 27 28 29 30 31
MARCH, 1980
Ati
14.49 4.60 2.62 1.01 .39 .10 3.19 1.15 .65 .29
<.l <1
.25 .49 .26 .70 .03 .24 .24 3.89 10.02 3.97 .63 1.79 <1 7.27 .38 1.22 1.40 .56 2.70
UCC 051421
Date
I 2 3 4 5 6 7 8 9 10 11
12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
APRIL, 1980
Ati
.44 .95 <1 .30 1.94 .13 .44 4.21 Down
N 99 II It N II
.70 .15 .11 .10 .24 .33 16.01 2.09 14.09 .95 .20 13 .97 1.10 8.40
ucc 05\422
*
t
Date
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
MAY, 1980
Ati
19.37 .80 .98 .60 .14
3.52 <1
1.36 .23
18.00 1.31 1.94 .29 .34 .27 .75
16.61 11.86 14.13 116.74 18.40 101.06
7.96 7.48 16.28 7.27 8.43 9.08 6.23 12.10 3.93
ucc 051423
Date
1
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
20
21 22 23 24 25 26 27 28 29 30
JUNE, 1980
Ati
<1 Down Down Down Down Down Down Down
<1
<.l
4.06 7.22
.30 1.80
.42 1.35 1.31
.66 1.25
.68 .75 .74 .83 1.73 5.85 12.65 4.24 4.48 1.65 7.68
UCC
051424
Date
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
JULY, 1980
Ati
26.95 10.07
3.69 7.01
.64 3.73
.75 .52 .44 .78 1.78 1.45 1.58 4.11 1.83 3.70 3.95 1.02 7.88 1.58 .24 3.27 1.84 2.22 .29 3.62 3.16 39.38 2.37 8.60 2.81
ucc 051425
Date
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
AUGUST, 1980
Ati
.73 .73 5.63 8.36 1.89 2.45 3.09 Down Down Down Down Down Down Down Down Down Down 5.62 4.97 4.97 <1 2.69 1.01 .51 2.12 2.03 7.59 44.42 8.09 4.53 .34
ucc 051426
UNION CARBIDE CORPORATION CHEMICALS AND PLASTICS
P.O.BOX 471. TEXAS CITY, TEXAS 77590
December 15, 1980
Mr. Bill Stewart Executive Director Texas Air Control Board 6330 Highway 290 East Austin, TX 78723
Subject: Semiannual Report for NESHAPS Regulation on.Vinyl Chloride Monomer, For Solvent Vinyl Resins Process, Texas City Plant (41 CFR 46559, October 21, 1976) Reporting Period: March thru August, 1980
Dear Mr. Stewart:
The attached Semiannual Report for March thru August 1980 is submitted in accordance with Section 61.70 of the Vinyl Chloride Regulation noted above.
I apologize for the delay in preparation and submittal of this report. Our Production Records group must necessarily be involved in the determination of the daily weighted average values of VCM content in the stripped varnish (A^, in order to incorporate the final official dally production quantities of the' various resins for the unit. There was an abnormally high turnover in the Production Records personnel at mid-year because s>f retirements, which required a realignment of responsibilities and training of new people. This caused a significant slowdown in their schedules and output, which has only recently begun to recover.
If there are any questions about this report, please refer them to my attention.
Very truly yours
JFE:1r Attachments
<J."F. Erdmann, P.E. Environmental Protection Coordinator (713) 948-5126
UCC
051427
UNION CARBIDE CORPORATION, SOLVENTS AND INTERMEDIATES DIVISION SEMIANNUAL REPORT FOR NESHAPS REGULATION
FOR VINYL CHLORIDE MONOMER SOLVENT VINYL RESINS PROCESS, TEXAS CITY, TEXAS
DECEMBER 15, 1980
I. EXCESS EMISSIONS r61.70 (cUDI
Under this section, parts A, B, and C do not apply as indicated in our March 15, 1979 semiannual report for the reasons listed therein. The solvent and monomer recovery system operations are the same as described In this previous report and will not be repeated here.
There were no emergency discharges during this reporting period.
II. CONTINUOUS STRIPPING rs61.70 (c)(2)]
The description of our monomer stripping system has been previously submitted in the semiannual report dated March 15, 1979.
The attached reports for the months of March through August, 1980 continue to support our previously stated position that our monomer stripping operations are far more efficient than the suspension process for which the analytical procedures in the Regulation were written. We have obtained the approval of your staff for a proposed once-per-week random sampling/analytical schedule In-order to reduce our analytical efforts to a more cost-productive basis. This request Is now fn the process of evaluation by EPA/Dallas, thru their various echelons. Including Washington headquarters and the Research Triangle Park sections. The data for this period Indicates the highest level recorded was 116 ppm on May 20th, which fs well within the 400 ppm upper limit. If necessary to help EPA/Dallas approve our previous request for the weekly analytical schedule, this data may be included with the previous 12 months for a total 18-month statistical analysis using the log-normal correlation.
OCC 0SU2Q
Date
1
2 3 4 5 6 7 8 .9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
MARCH, 1980
Ati
14.49 4.60 2.62 1.01 .39 .10 3.19 1.15 .65 .29
<1 <1
.25 .49 .26 .70 .03 .24 .24 3.89 10.02 3.97 .63 1.79 <1 7.27 .38 1.22 1.40 .56 2.70
0SAA29
Date
1 2 3 4 5 6 7 8 9 10 11
12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
APRIL, 1980
Ati
.44 .95 <1 .30 -1.94 .13 .44 4.21 Down
It II It It - If II
.70 .15 .11 .10 .24 .33 16.01 2.09 14.09 .95 .20 .13 .97 1.10 8.40
ucc 051430
Date
1
2 3 4
5
6 7 8 9 10 11 12 13 14 15 16 17 18 19
2Q
21 22 23 24 25 26 27 28 29 30 31
MAY, 1980
Ati
19.37 .80 .98 .60
.14 3.52 <1 1.36
.23 18.00
1.31 1.94
.29 .34 .27 .75 16.61 11.86 14.13 116.74 18.40 101.06 7.96 7.48 16.28 7.27 8.43 9.08 6.23 12.10 3.93
UCC
051431
Date
1
2 3 4
'S
6 7 8
9
10 11 12 13 14 15 16 17 18 19 20 21
22
23 24 25 26 27 28 29 30
JUNE, 1980
Ati
<1 Down Down Down Down Down Down Down
<1
<1
4.06 7.22
.30 1.80
.42 1.35 1.31
.66 1.25
.68 .75 .74 .83 1.73 5.85 12.65 4.24 4.48 1.65 7.68
UCC 051432
Date
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 m 21 22. 23 24 25 26 27 28 29 30 31
JULY. 1980
Ati
26.95 10.07
3.69 7.01 -.64 3.73
.75 .52 .44 .78 1.78 1.45 1.58 4.11 1.83 3.70 3.95 1.02 7.88 1.58 .24 3.27 1.84 2.22 .29 3.62 3.16 39.38 2.37 8.60 2.81
UCC 051433
Date
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
AUGUST. 1980
Ati
.73 .73 5.63 8.36 1.89 2.45 3.09 Down Down Down Down Down Down Down Down Down Down 5.62 4.97 4.97 <1 2.69 1.01 .51 2.12 2.03 7.59 44.42 8.09 4.53 .34
UCC
051434
f) M
Mvsm - //>//& *f**t/n
_______ fiJsmf/S*vf *-4**t. fi*f*f*
^___
' ^C*nlpU& rf cUJ 5 *dU \&ri*~&)
\
LtlL T* /V. faMtnJ &i?4 ~ *//& -
______ dl*d r. -W dtm t~ J&iduJ U**U____
3) nf n iT7*!q/##r*-___
*ufoi^j M *Jw*s Ai*ut> -szHTsyu** c***e*ut*L.
4 t-rr * ja#***
J* ~--$A/m M?Jn
ianUtCt, <y T**f /V.
s) &*- & #*' Vrfht&dinf. )fc,, //f
/*72U#y 2&u
-BUN..
UCC 051435
Mr. Jim Bodamer November 6, 1980 Page 2
Mr. Martin Brittain of EPA/Dallas has indicated he has forwarded the latter information which the TACB has approved to appropriate sections in both the RTP and Washington offices for their review and approval before they make a decision from the Dallas location.
We would appreciate any support you can provide for this request and similar ones for which the original NESHAPS regulation was not parti cularly written. We will be pleased to provide any additional informa tion and/or conduct an inspection of these facilities with you to resolve any pertinent questions that may arise. Thank you for your interest in this problem.
%rv. Erdmann, P.fc. Environmental Protection Coordinator (713) 948-5126
JFE:ir Attachments cc: (cover letter only)
Mr. Martin Brittain, EPA/Dallas Mr. John W. Key, TACB/Austin Mr. Sabi no Gomez, TACB/Bellaire
bcc: (cover letter only) R. M. Arnold J. H. Barrett W. T. Gray, Jr. J. B. Leverton/J. S. Knight R. R. Rankin - CLC D. R. Reem
Dr. D. G. Reese/P. D. Smith G. F. Tacquard/S. A. Dickerson L. B. Feldcamp - Baker & Botts
ucc
051437
Mr. Jim Bodamer November 6, 1980 Page 2
Mr. Martin Brittain of EPA/Dallas has indicated he has forwarded the latter information which the TACB has approved to appropriate sections in both the RTP and Washington offices for their review and approval before they make a decision from the Dallas location.
We would appreciate any support you can provide for this request and similar ones for which the original NESHAPS regulation was not parti cularly written. We will be pleased to provide any additional informa tion and/or conduct an inspection of these facilities with you to resolve any pertinent questions that may arise. Thank you for your interest in this problem.
<arf. Erdmann, P.fc. Environmental Protection Coordinator (713) 948-5126
JFE:ir Attachments cc: (cover letter only)
Mr. Martin Brittain, EPA/Dallas Mr. John W. Key, TACB/Austin Mr. Sabi no Gomez, TACB/Bellaire
bcc: (cover letter only) R. M, Arnold J. H. Barrett W. T. Gray, Jr. 0. B. Leverton/J. S. Knight R. R. Rankin - CLC D. R. Reem
Dr. D. G. Reese/P. D. Smith G. F. Tacquard/S. A. Dickerson L. B. Feldcamp - Baker & Botts
ucc 051437
INTERNAL CORRESPONDENCE
P. O. BOX 471, TEXAS CITY, TEXAS 7 7 390
To: Messrs. R. M. Arnold
October 21, 1980
0. H. Barrett
W. T. Gray, Or.
0. B. Leverton/0. S. Knight
R. R. Rankin - CLC
D. R. Reem
Dr. D. G. Reese/P. D. Smith
G. F. Tacquard/S. A. Dickerson
Copy to:
J. L. Hansen - 511
Subject: Request for Change in Sampling and Analytical Program Under Part 61, NESHAPS Regulation for Vinyl Chloride Monomer Control (TACB Account No. SB-0076-0)_____________________ ____________
Gentlemen:
Attached Is the response we have been awaiting from TACB as the first step in getting this test program operating In a cost effective manner. As you can see from this letter, the supplemental Information we submitted In August based on 01m Hansen's application of the log-normal distribution was a major factor In obtaining this approval. For 01m's help In coming up with this approach, I am highly appreciative.
I plan to contact Mr. Brittain at the Dallas EPA office In a few dys to see what new problems may appear In this scenario. If any suggestions or comnents are cluttering up your thoughts, please send them to me.
/ Very truly yours.
///*?/ i&77&4/
&*/**<**
fa/y) 76?-*'*sS'
j
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ucc
051438
TEXAS AIR CONTROL BOARD
JOHN L. BLAIR Chairman CHARLES R. JAYNES Vice Cheirnten
BILL STEWART, P. E. Executive Director
6330 HWY. 290 EAST AUSTIN, TEXAS 78723
512/451-5711
WILLIAM N. ALLAN VITTORIO K.ARGENTO.P. E.
FRED HARTMAN
0. JACK KILIAN, M. 0. OTTO R. KUNZE, Ph. D., P, E.
FRANK H. LEWIS WILLIAM 0. PARISH
October 14, 1980
Mr. Martin Brittain, P. E. NESHAP Coordinator 6AEAE United States Environmental Protection Agency Region VI 1201 Elm Street Dallas, n 75270
RECEIVED
,'ip.T 2 0 i960 J. F. E.
\
Re: Union Carbide Corporation Alternative Testing Method
Texas City, Galveston County
TACB Account No. GB-0076-J
Dear Mr. Brittain:
I am forwarding to you a request by Union Carbide for a change In the sampling and analytical procedures specified In Part 61, Subparts A and F and Appendix B, Methods 106 and 107. My staff reviewed the original request and found it to be deficient; however, supplemental information provided by Union Carbide now seems to support the re quest. We are recommending approval of the proposed procedure and have enclosed copies of all pertinent documents for your considera tion.
If we can be of further assistance, please contact Mr. Charles Shevlln of my staff at extension 251. Please advise us of your final de termination concerning this matter.
1
John W. Key, p. E., Chief Source Evaluation Section
Enclosures
cc: Mr, Cecil Bradford, Compliance Division Mr. Sabino Gomez, Region 7 Mr. J. F. Erdmann, P. E,, Union Carbide Corporation
UCC
051439
internal correspondence QUALITY ASSURANCE
TEXAS CITY PLANT
Copy to
Mr. S. A. Dickerson Dr. D. G. Reese Mr. P. D. Smith/
Mr. J. R. Rex Mr. G. F. Tacquard
Date
rccswfp
SEP 22'380
J.F.E.
September 18, 1980 Vinyls Lab - Texas City
Jack:
Steve informed me of your request to lower from 400 ppm to 250 ppm, the point at which the Q.C. Laboratory will automatically recheck the ppm VCM value on any stripping still sarrple frcm Bldg. 117.
To comply with this request, effective today the Laboratory SOP will be revised to state that any stripping still sample which exceeds 250 ppm VCM will automatically be rechecked.
We hope this revision will be of assistance to you in your con tinuing effort to attain a reduction in sampling/analyzing fre quency .
Please advise if we can be of any further assistance.
Regards,
GEV/pl
G. E. Vaughan
CHEMICALS AND PLASTICS
Occ
d TiLO STift Cf&fitK) - 74u
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ft faf4 ^ far?*
TfoS Ats dfipsT+J %L* ju^puJhf-
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UCC
051441
ucc 051442
^yrtjk- vr T7^e, mw
y
Jit* &Y '
sujz, .
ut &* Utsr&&tiD SZ,,.
polls.
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UCC
051444
UNION CARBIDE CORPORATION CHEMICALS AND PLASTICS
P.O.BOX 471, TEXAS CITY. TEXAS 77590
August 6, 1980
'**} aijuttcwHS /--
Mr. John W. Key * Source Evaluation Section Texas Air Control Board 6330 Highway 290 East Austin, TX 78723
Attn:
Mr. Charles B. Shevlin
Subject: TACB Account No. GB-0076-J, Request for Change in Sampling and Analytical Program Under Part 61, NESHAPS Regulation for Vinyl Chloride Monomer Control
Gentlemen:
Following the receipt of the letter of May 20, 1980 from James P. Draper in response to our original requests for a change in the analytical schedule under this regulation, we submitted the data to our statistical staff in the R and D groups at the South Charleston Technical Center. They have evaluated the data in the same manner we did and have shown, as you did, that the distribution by that method is not normal and the first set of conclusions we reached were not
proper.
However, in addition, they have used a computer program for a log-normal distri bution and applied the same statistical tests to this manner of computation. These new results show that the statistical analysis, when applied to the log arithms of the daily data values, does exhibit a log-normal distribution and the previous method of evaluation and determination of adequate samples for a 99.935 confidence level can be used. From this, we can show that if a total of six samples is taken in a six month period and the geometric mean value does not exceed 35 ppm, we have 99.9% confidence that the 400 ppm limit has not been
exceeded.
On this basis we are still willing to proceed with weekly random sampling (one day out of seven), which is over four times more frequent than the statistical data indicate is necessary. Provided we analyze samples on this basis of one day put of every seven for a total of 26 tests every six months, we have 99.9% confidence that the 400 ppm level has not been exceeded, if the geometric mean of the 26 samples comes out to less than 124 ppm. The statistical evalua tion by our Technical Center group which supports these statements is attached for your inspection and review.
In connection with the randomness of sampling and analysis, the following is our preferred method:
Ucc
051445
Mr. John W. Key August 6, 1980 Page 2
1) The sampling schedule will not be changed from the present, which calls for a stripped varnish sample from each stripper for each regular shift of operation. We have four strippers and three shifts/day, which results in up to 12 samples/day, depending on how many strippers are operating. These samples will be sent directly to the laboratory In the usual manner.
2) The laboratory will provide a random analytical schedule for one day out of
seven to be predetermined on a weekly basis for selecting which day the
varnish samples will be run. We must operate on a weekly schedule to optimize our manpower needs in the laboratory and eliminate as much overtime
as possible.
Please review the attached documents and let me know ef any problems you see which could limit your support for this request. We understand any official
changes in the regulation must be approved by the EPA, and to that end we plan to submit this same request and information to the TRW contractor's team that
is presently scheduled for a review of the NESHAPS regulation at our plant in
the near future. If you have any suggestions for ways to speed up this approval
process, please share them with us.
0FE:ir Attachments cc: Mr. Howard Houston, TACB, Austin1'
Mr. Sabi no Gomez, TACB, Belial re * Dr. E. R. Ibert, GCACD *
VJ. F. Erdmann, P.E. Environmental Protection Coordinator (713) 948-5126
bcc: R. E. O'Bryan/NESHAPS (VCM) File *J. B, Leverton/J. S. Knight *J. H. Barrett
G. F. Tacquard/S. A. Dickerson / *R. M. Arnold *D. G. Reese *P. D. Smith
R. R. Rankin - CLC ' *W. T, Gray, Jr. *D. R. Reem
* cover letter only fCn? Hi ;7 -
4- **"
ucc 051447
UNION CARBIDE
INTERNAL CORRESPONDENCE
CHEMICALS AND PLASTICS
P. O. BOX 8361, SOUTH CHARLESTON, WEST VIRGINIA 25303
Jack Erdmann, Texas City
July 22, 1980
John Leverton Charlie Hendrix
Statistical Evaluation of
Vinyl Chloride Data for Solvent Vinyl Resins Stripping - Use of Lognormal Distribution
Dear Jack:
I have analyzed the Vinyl Chloride concentration data you sent me. I am returning 3 attachments with this letter: a rewrite of your April letter to the Texas Air Control Board using all the data and log normal statistics; copies of computer printouts; and a copy of a discussion of the lognormal distribution from a NIOSH publication (number 77-173).
The raw data are not normally distributed (Kolmogoroi-Smirnov D = 7.58, which is significant at the 99.99% level). However, when this Ate--sAt -isa applied Atoa AthUea 1logari+thWhraipsof fthhfet Hdiaf-ata, wet,iA find*? /4 HD a= .Q9^3, uwhhi ich lisC not significant impling the data an*e normally distributed.
/s 7
. _ ,, /) ^
Therefore, the data should be transformed before analyzing, and the statistics which should be used when reporting these data are the geometric mean (GM) and the geometric standard deviation (GSD). The GM corresponds to the median or middle of the distribution and for these data is a better indication of the distribution's center than the arithmetic average.
The calculations you performed before are all valid for log normal distributions, and the final results can be transformed back to the original scale by taking antilogarithms.
Another simple way to look at these data are simply to rank the scores and look at percentiles. For example, 99% of this years data are less than 200 ppm. I Included a printout of the ranked data so that you can see the distribution.
If I have been too terse, and you have questions, please call.
Sincerely,
JH:dm Attachments
r
Jim Hansen
IJCC
051448
DATA EVALUATION, MARCH 1979 - FEBRUARY 1980
Individual twenty-four hour weighted average VCM concentrations (dry resin basis), At^, were determined and reported for this period in our last two Semiannual Reports.
The following statistical parameters were determined from these daily VCM concentrations:
1) Number of daily average values of Aj^ = n = 364
2) Geometric Mean, = 2J_ ppm
3) Geometric Standard Deviation, $g = 6.88
4) Predicted upper range for geometric mean values, 99% confidence level.
Z for 99% level - 2.33, for n "7 30 upper limit only.
1n(vg) - ^771
Vg * hi
This valuation indicates that the Geometric mean value for the VCM concentrations based on this years data period would be below 2.2 ppm 99% of the time. This compares to an upper limit of 400 ppm specified by the regulation.
Vg - ln(maximum specification level) Determine t -
standard deviation, Sg
.752 - 5.99 1.93
-5.24 = -2.72
1.93
However, from Table A in the text, a t-value of -3.1 Is shown for a 99.9% confidence level (0.0010).
By using the following notation, a calculation can be made to determine the sample size (n), which would provide 99.9% confidence that we would not exceed the 400 ppm limit.
Let a * risk of rejecting an acceptable value * 0.001 and
let 8 * risk of accepting a rejectable value * 0.001
for a = 0.001, T] = 3.1 = In K - v In K - .752
(A)
1.93
fiT
-2-
For 3 = 0.001, T2 3 -3.1 = In K - upper limit = In K - 5.99
Sv 1.93
FT
Subtracting equation (A) from equation (B):
T2 - T] 3 -3.1 - (3.1) 3 In K - 5.99 - In K - .752
1.93
1.93
(B)
-6.2 = In K - 5.99 - In K + .752 1.93
-5.24 1.93
6.2 3 5.24 fn~ 1.93
frT 2.29 n 3 5.23
(just over five samplesrequired)
This value for n is slightly greater than 5, so a sample of 6 is the next nearest whole number.
If we use this value of n 3 5.23 to solve for K, the mean value of
Ayi that would assure not exceeding 400 ppm more than 0.1% of the time, we get the following:
-3.1 = In K - 5.99
-3.1 3 In K - 5.99
1.93 272?
.843
In K - 5.99 3 -2.62; In K 3 3.38; K 3 29.4
However, we can't take part of a sample, so using n 3 6, iffT3 2.45
-3.1 3 In K - 5.99
-3.1 3 In K - 5.99
1.93 TM
.788
In K - 5.99 3 -2.44
K 3 34.8
which Is the value of Ay. for six samples for every six months reportlnq period below which there Is ovir 99.9% confidence that the 400 ppm llnrit has not been exceeded.
However, we plan to sample once per week to get Ayi for a regular 3-shift day, sampling each stripper each shift for a total of 12 samples from which one weighted average concentration can be deter mined for that day. In six months, 26 such At-| values would be available, and if their mean value doesn't exceed the following K value, there is
UCC
051450
3- -
99.9% chance that all values are below the 400 ppm limit.
-3.1 = In K - 5.99
1.93
nr------------------
= In K - 5.99
1.93 TT
- In K - 5.99 .378
-(3.1) (.378) = In K - 5.99 = -1.17
or In K = 4.82 or K = 124 ppm (Geometric Mean)
ucc
051451
TECHNICAL APPENDIX M*
NORMAL AND LOGNORMAL FREQUENCY DISTRIBUTIONS
The statistical methods discussed in this man munity air pollution environmental data are
ual assume that concentrations in random occu better described by a lognormal distribution.
pational environmental samples are lognormally That is, the logarithms (either base e or base
and independently distributed both within any 10) of the data are approximately normally
particular workshift and over many daily expo distributed. Most importantly, Breslin et al.
sure averages. Additionally, it is assumed that (M-10), Sherwood (M-ll, M-12), Jones and
the sampling and analytical errors of an indus Brief (M-13), Gale (M-14, M-15), Coenen (M-16,
trial hygiene measurement sample are normally M-17), Hounam (M-18), and Juda and Bud^
and independently distributed. The technical zinski (M-19, M-20) have shown that occupa
reasons for the choice of these two distributions tional environmental data from both open air
for modeling our data distributions are given and confined work spaces for both short (sec
below. There is nothing sacred about the choice onds) and long (days) time periods are log-
of these distribution models. They were chosen normally distributed.
because they occur very frequently in indus What are the differences between normally
trial hygiene applications, and they are easy and lognormally distributed data? First, it
to use because their properties have been thor should be remembered that a "normal" distri
oughly investigated. The empirical observation bution is completely determined by the arith
that the data usually are well-fitted by the metic mean p and the standard deviation <r of
normal and lognormal models is no guarantee the distribution. On the other hand, a lognormal
that all data fit these models. If there is any distribution is completely determined by th
doubt about the appropriate application of the median or geometric mean <GM) and the geo
normal or lognormal model, the first step in metric standard deviation (GSD). For log-
the data analysis should be to sketch a distri nonnally distributed data, a logarithmic trans
bution histogram or use probability paper as formation of the original data is normally
discussed in Technical Appendix I. Also refer distributed. The GM and GSD of the lognormal
to Technical Appendix I for examples of data distribution are the antilogs of the mean and
that might not be adequately described by the standard deviation of the logarithmic trans
lognormal model.
formation. Normally distributed data have a
Before sample data can be statistically ana symmetrical distribution curve whereas log-
lyzed, we must have knowledge of the fre normally distributed environmental data are
quency distribution of the results or some as generally positively skewed (long "tail" to the
sumptions must be made. Roach (M-2-M-4) right indicating a larger probability of very
and Kerr (M-5) have assumed that environ large concentrations when compared with a
mental data are normally distributed. However, lower probability expected of normally dis
it is well established (M-fi-M-9) that most com- tributed data). Figure M-l compares a log
normal distribution to a normal distributi n
Thi* material in part was originally presented in with the same arithmetic mean p and standard
Leidel and Busch, Exposure Measurement Action Level and Occupational Exposure Variability (NIOSH Tech
nical Information, HEW Publication No. (NIOSH) 78-131, Cincinnati, Ohio, December 1970) and Refer ence M-l.
deviation r. The conditions conducive to (but not all necessary for) the occurrence of log normal distributions are found in occupational
122 UCC
051452
** ' Figure M-l. Lognormal and normal distributions with the
same arithmetic mean and standard deviation.
environmental data (M-16). These conditions When several samples are taken in a plant
are that
to determine the average concentration of the
the concentrations cover a wide range of contaminant and estimate the average exposure
values, often several orders of magnitude, of an employee, the lognormal distribution the concentrations lie close to a physical should be assumed. However, the normal dis
limit (zero, concentration),
tribution may be used in the special cases of
the variation of the measured concentra taking a sample to check compliance with a
tion is of the order of the size of the ceiling standard, and taking a sample (or sam
measured concentration, and
ples) for the entire time period for which the
a finite probability exists of very large standard is defined. In these cases, the entire
values (or data "spikes") occurring.
time interval of interest in represented in the
The variation of occupational environmental sample, with only normally distributed sam
data (differences between repeated measure pling and analytical variations affecting the
ments at the same site) can usually be broken measurement
into three major components: random errors The relative variation of a normal distribu
of the sampling method; random errors of the tion (such as the random errors of the sampling
analytical method; and variation of the environ and analytical procedures) is commonly meas
ment with time. The first two components of ured by the coefficient of variation (CV). The
the variation are usually known in advance and CV is also known as the relative standard devia
are approximately normally distributed. The tion. The CV is a useful index of dispersion in
environmental fluctuations of a contaminant in that limits consisting of the true mean of a set of
a plant, however, usually greatly exceed the data, plus or minus twice the CV, will contain
variation of known instruments (often by fac about 99% of the data measurements. Thus, if an
tors of 10 or 20). The above components of analytical procedure with a CV of 10% is used
variation were discussed in an article by to repeatedly measure some nonvarying physi
LeClare et al. (M-21).
cal property (such as the concentration of a
123
UCC 051453
chemical in a beaker of solution), then about 95% of the measurements will fall within plus or minus 20% (2 times the CV) of the true con centration.
Unfortunately, the property we are trying to measure -- the employee's exposure concen tration -- is not a fixed physical property. The exposure concentrations are fluctuating in a lognormal manner. First, they are fluctuating over the 8-hour period of the TWA exposure measurement. Breathing zone grab samples (samples of less than about 30 minutes' dura tion, typically only a few minutes) tend to reflect the environmental variation within a day so that grab sample results have relatively high variation. However, this variation in the sam ple results can be eliminated by going to a full period sampling strategy as discussed by Leidel and Busch (M-l). Second, the day-to-day vari ation of the true 8-hour TWA exposures is also lognormally distributed.
Environmental variation is expressed by the GSD. A GSD of 1.0 represents absolutely no variation in the environment. GSD's of 2.0 and
above represent relatively high variation. Hald (M-22) states that the shape of lognormal dis tributions with low variations, such as those with GSD's less than about 1.4, roughly approxi mate normal distribution shapes. For this range of GSD's, there is a rough equivalence between the quantity (GSD --1) and the CV, as follows:
GSD
(GSD-1)
CV
1.05 0.05 0.049 1.10 0.10 0.096 1.20 0.20 0.18 1.30 0.30 0.27 1.40 0.40 0.35
For those interested in a detailed study of the lognormal distribution, Ajtchinson andt Brpwn (M-23)_is an excellentjreference. Figure M-2 shows four different lognormal distributions that share a common arithmetic mean of 10 ppm. Four different variations are shown with GSD's of 12, 1.5, 2.0, and 3.0.
Figure M-2. Lognormal distributions for arithmetic mean con centration of 10 ppm.
124
ucc
0S14S4
CONVERSION FORMULAS FOR A
GSD = antilogio (<n) where (logl0 x) was
LOGNORMAL FREQUENCY DISTRIBUTION
used. The conversion relations between the
If the variable (In x) is normally distributed above six parameters are given in Table M-l.
(the variable x has a lognormal distribution),
we can define
Notes:
y. -- true arithmetic mean of x-distribu- 1. The relations apply only to the true para
tion meter of the parent distribution. They should
it=true standard deviation of x-distri- not be used for parameters of a sample except
bution
as a very rough approximation.
/ti--true arithmetic mean of (In x) 2. The GM and GSD are used to describe para
values
meters of either a sample or the parent distri
<n = true standard deviation of (In x) bution, but they cannot be used in the relations
values
unless they are calculated from the true parent
GM = geometric mean of x-distribution distribution.
GSD -- geometric standard deviation = exp 3. The GSD of the x-distribution is the same (<ri) where (In x) was used to cal regardless of whether base 10 or base e loga
culate V|
rithms were used to calculate v,,
TABLE M-1. CONVERSION RELATIONS BETWEEN LOGARITHMIC PARAMETERS AND ARITHMETIC PARAMETERS OP A LOGNORMAL DISTRIBUTION
Given
To obtain
llM
fit
GM-
exp On)
GM-
M*
<n
GSD-
exp (a,)
exp^
+
GSD =
m> vi GM,i
exp On + -|"<n*) (GM) exp (-|- <n*)
Pfc vi
[exp (2w+i*)l [exp (<n*) -- 1]
GM, a.
(GM)* [exp (n*)J [exp (<n*) -1J
\
GM In (GM)
In /l-- T***
GSD
In (GSD)
n* yj ina+7-)
.V|
mode
exp (m -- a?) -- most frequent value
129 UCC 051455
VARIABLE conc
MOMENTS
N MEAN STD DEV
SKENESS
ss
cv t:hean=o
p:iNNORMAL
365
14.9)98 55.6855
7.66602 1209968 373.231
5.1108 7.56414
'aOM *liTS
^UM VARIANCE
KUHTOSIS CiS STD Mt AN PHOb>|TI
PHOBU
Uti(ki<|nY-!M>'rMY 6-t^Al/v.
bar chart
600**
STATISTICAL ANALYSIS UniVAhIATE
SYSTEM
15!46 MONDAY JULY 21> 1900
365 5445.74 3100.68
73.442 1126719 2.91471
0.0001
(07o^oop
1004 MAA 754 03 504 nEl) 256 U1 06 MIN
RANGE 03-01 MOUE
itj
quantiles
611.95 7.165 2.24
0.4525 0
011.95 6.7125
0.1
99* *b* 90*
10* b* 1*
dOAPLOT
2
191.033 51.9441 22.9797
0.115 O.J
0.0624999
600*
LOWEST 0<
0.031 0.031 0.06 (
0. 1 (
EXTREMES
ID 261 5) 25) 24) 2)
HIGHEST
181.661 206.451
368.21 596.671 611.951
ID
25) 26)
29) 4) 4)
NORMAL PROBABILITY PLOT
Da^tc VLrf'
value COUNT
01
0.03
2
n.os
1
0.1 31
n.n
1
0.12
2
0.13
3
0.14
2
4.15
2
0.17
1
0.18
2
0.19
1
0.2 2
0.22
2
0.23
3
0.25
1
0.26
2
0.27
4
0.28
3
0.29
2
0.3 1
PERCENTS CELL CUM
0.3 0.3 0.5 0.8
0.3 1.1 8.5 9.6 0.3 9.9
0.5 10.4
O.H 11.2 0.5 11.6 0.5 12.3
0.3 12.6 0.5 13.2 0.3 13.4
0.5 14.0 0.5 14.5
O.h 15.3 0.3 15.6 0.5 16.2 1.1 IT.3 0.6 16.1
0.5 18.6 0.3 1 d.9
300*
1
7 3
6
345
-2 -1
FREQUENCY TABLE
VALUE COUNT
0.31
i
0.32
0.33
0.34
11.35
3
0.37
I
0.36
0.4 0.41
1
c
0.43
0.44
I
0.45
J
0.4O
1
0.4 7
i
0.46
I
0.51
0.52
0.55
1
0.5b
0.57
I
0.58
PERCENTS CELL CUM
0.3 19.2 0.5 19.f 0.5 20.3 0.5 20.8 0.8 21.6
0.3 21.9
0.5 22.5 0.3 22.7 0.5 23.3 0.5 23.8 0.3 24.1
0.8 24.9
0.3 25.2 0.3 25.5
0.3 25.8 0.5 26.3 0.5 26.6 0.3 27.1 0.5 27.7 U 3 27.9
0.5 26.5
.
VALUE COUNT
0.59
1
0.64
3
0.65
2
O.bT 0.69
1 1
0.71
3
0.78
1
0.83
1
0.84
1
0.86
1
0.67
1
o.bb
1
0.91
2
0.92
1
0.93 0.97
1 1
1 1.04
1 1
1.06
1
1.1 1
1.11
1
PEHCENTS CELL CUM
0.3 28.8 O.B 29.6
0.5 30.1 0.3 30.4 0.3 30.7
0.8 31.5
0.3 31.8
u.3 32.1 0.3 32.3 0.3 32.6 0.3 32.9 0.3 33.2 0.5 33.7
0.3 34.0
0.3 34.2 0.3 34.5 0.3 34.6
0.3 35.1 0.3 35.3 0.3 35.6
0.3 35.9
*1
value
1.15 1.18
1.2 1.22 1.29 1.31 1.35 1.37 1.38
1.4 1.41
1.43 1.46 1.49
1.5 1.52 1.58 1.63
1.66 1.69 1.73
COUNT 2 1 1 1 3
1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1
PERCENTS CELL CUM
0.5 36.4 0.3 3o . 7 0.3 37.0 0.3 37.3 0.6 36.1
0.3 38.4 0.3 36.6 0.3 3b.9 0.5 39.5 0.3 39.7 0.3 40.0
0.3 40.3 0.5 40.6 0.3 41.1
0.3 *1.4 0.3 41.6 0.3 41.9 0.3 42.2
0.3 42.5 0.3 42.7
0.3 43.0
ucc
051456
ucc
051457
VARIABLE CONC
value COUNI
1.75
1
1.76
1
1.77
.1.79
1 b1
1 1 1
l.bb
1
1.B9
1
1.91
I
1.92
1
1.93
2
1.95
1
1.99
1
2.02
1
2.03
2
2.04
1
2.07
1
2.11 2.12 2.16
1
1
2.19
1
2.2
1
2.21
1
2.27
1
2.28
1
2.32
1
2.33
1
2.36
1
2.37
1
2.4 1
2.41
1
2.43
1
2.45
1
2.51
1
2.52
1
2.54
1
2.68
1
2.7 1
2.71
1
2.74
l
2.8
1
2. b5
1
2.86
1
2.87
1
2.89
1
2.93
1
2.96
1
2.99
1
31
3.02
1
3.12
1
PERCtMTS
cell CUM
. >0.3 43.3
0 43.6
U. 4 43.8 U.3 44.1
U.3 44,4
0.3 44,7 U.3 44.9 0.3 45.2 0.3 45.3 U.5 46.0
0.3 4b.3 0.3 46.6 0.3 46.6
0.3 47.4 0.3 47.7 0.3 47.9
0.3 46.2 U.3 48.5 0.3 49.0
0.3 49.3 0.3 49.6 0.3 49.9 U.3 50.1 0.3 50.4 0.3 50.7 0.3 51.0 0.3 51.2
0.3 51 .5 0.3 51.8 0.3 52.1 0.3 52.3 u.3 62 6 0.3 52.9 0.3 53.2 0.3 53.4 0.3 53.7 0.3 54.0 0.3 54.2
0.3 54.5 0.3 54.6
u.3 65.1 0.3 55.3 0.3 55.6 0.3 55.9 0.3 56.2 0.3 56.4 0.3 56.7 0.3 57.0 0.3 57.3 0. 3 57.6
A
aT A ! I b
I CAL
analysis
univariail
SYSTEM
FREQUENCY TABLE (CUNT.)
PERCENTS
VALUE COUNT CELL CUM
J. 13
1 U.j 57.B
3.23
1 0.3 56.1
3.25
1 U.J 56.4
3.26
1 U.3 56.6
J.26
1 U.3 56.9
3.31
1 0.3 59.2
3.34
1 0.3 59.5
3.3b
1 0.3 59.7
3.4b
1 U.3 60.0
3.49
1 U.3 60.3
3.51
1 0.3 60.5
3.52
2 0.5 61.1
3.67
2 0.6 61.6
3.76
1 0.3 61.9
3.B9
1 0.3 62.2
4.06
1 0.3 62.5
4.07
1 0.3 62.7
4.09
1 0.3 63.0
4.19
1 0.3 63.3
4.2
1 0.3 63.6
4.3
1 0.3 63.8
4.33
1 0.3 64.1
4.3e
1 0.3 64.4
4.37
1 0.3 64.7
4.4b
1 0.3 64.9
4*h9
2 0.5 65.5
4.6
1 0.3 65.8
4.6
1 0.3 66.0
*.9
1 0.3 66.3
4.99
1 0.3 bb.6
5.02
1 . 0.3 66.6
6.17
1 U.3 67.1
5.33
1 0.3 67.4
6.44
1 0.3 67.7
6.51
1 U.J 67.9
6.57
1 0.3 68.2
5.5b
1 0.3 bb.6
3.66
1 0.3 68. B
5.74
1 o.i 69.0
5.79
1 0.3 69.3
5.bB
1 U.3 09.6
5.97
2 0.5 70.1
6.12
1 0.3 70.4
6.33
1 0.3 70.7
6.42
1 0.3 71.0
6.44
2 U.5 71.5
6.49
1 0.3 71.6
6.64
1 U.3 72.1
b. 7a
1 0.3 72.3
6.7o
1 0.3 72.6
value CDUN1
6.77
1
6.62
1
6.86
1
6.69
1
6.9 1
6.91
1
7.15
2
7.17
1
7.31
1
7.45
1
7.61
7.6b
1
7.67
1
7.93
1
b.01
1
6.36
1
B.46
1
6.5
1
6.57
1
b.58
1
8.73
1
6.79
8.9
1
9.02
1
9.13
1
9.42
1
9.47
9.5
1
9.59
2
9.73
1
9.91
1
10.21
1
10.28
1
10.76
1
11.02
1
11.6
2
11.67
1
11.66
1
12.4?
1
12.7
1
13.28
1
13.47
1
14.35
1
14.4
1
15.71 % 1
16.72
1
17.14
1
17.15
1
17.52
1
1 7.56
1
PERCENTS CELL CUM
0.3 72.9 0.3 73.2 0.3 73.4 U.J 73.7
0.3 74.0 0.3 74.2 0.5 74.8 0.3 75.1
0.3 75.3 0.3 75.6
0.3 75.9 0.3 76.2 0.3 76.4
0.3 76.7
0.3 77.0 0.3 77.3 0.3 77.5
0.3 77.6 0.3 76.1 0.3 78.4 0.3 78.6 0.3 78'. 9
0.3 79.2
0.3 79.5 0.3 79.7 0.3 60.0 0.3 80.3 0.3 60.5 0.5 61.1 u.3 61.4 u.3 61.6 U.3 61.9
0.3 62.2 0.3 62.5
0.3 62.7 0.5 63.3 0.3 63.6
0.3 63.6 0.3 64.1 U.3 84.4 0.3 84.7 0.3 84.9 0.3 65.2
0.3 65.5 0.3 85.6 0.3 86.0 0.3 86.3
0.3 66.6 0.3 86.8 0.3 67.1
15S46 MONDAYt JULY 21, i960
2
value count
IT.97
1
18.06
1
16.14 16.58
1 1
16.66
1
18.8
1
19.3
1
20.54
1
20.76
1
22.4
1
23.56
1
23.7
1
24.71
1
25.41
1
26.06
1
27.33
1
30.33
1
30.87
1
31.61
1
31.71
1
32.52
1
34.6
1
37.36
1
37.66
1
40.56
1
41.84
1
43.73
1
49.26
1
52.84
1
54.93 56.61
1 1
60.62
1
73.9
1
114.73
1
118.33
1
134.67
1
147.27
1
167.13
1
168.35
1
173.59
1
176.05
1
178.76
1
181.66
1
206.45 368.2
1 1
596.67
1
611.95
1
PERCENTS
cell CUM 0.3 67.4
0.3 87.7
0.3 87.9 0.3 86.2
0.3 66.5 0.3 66.8 U.3 69.0 0.3 89.3 0.3 69.6 0.3 69.9
0.3 90.1 0.3 90.4 0.3 90.7
0.3 91.0
0.3 91.2 0.3 91.5
0.3 91,6 0.3 92.1 U.3 92.3 0.3 92.6 0.3 92.9 0.3 93.2
0.3 93.4
0.3 93.7 0.3 94.0 0.3 94.2
0.3 94.5 0.3 94.8 0.3 95.1 0.3 95.3 0.3 Vb.b 0.3 95.9
0.3 96.2 0.3 96.4 0.3 Vb.7 0.3 97.0 0.3 97.3 0.3 97.5 0.3 97.6 0.3 96.1 0.3 96.4 0.3 98.6 0.3 96.9 0.3 99.2 0.3 99.5
0.3 99.7 0.3 100.0
STATISTICAL ANALYSIS SYSTEM
15146 MONDAY* JULY 21* 1980
iogtC'
UNIVARIATE
VARIABLE LNCONC
MOMENTS
MEAN SID DEV SKE^NISS
ss cv
T:MEAN=o o:normal
364
0.752126 1.929*6
0.3)9412
1SS7.33 256.536 7.43707
0.9304JS
SUM wGTS SUM VARIANCE *UHTOSIS
CSS STO MEAN
*>ROG> 11 I
R*OB>U
Jb4
273.775 3.7229
0.237927 1351.41
0.101132 0.0001
QUANTILES
1004 75 SO* 254 0*
MAX Ui MEU ul
min
b.41bb5 1 .9099
Q.biWb -0.776529
-3.50656
RANGE
U3-U1 MODE
9.92321
2.7*643
-2.3U2b&
994
9b* ^ 90* f 10*
b* 14
b*2bI64 >/ r J.9
3.139JS -2.1202b -2.3023b -2*38292
LOtST
-3.50656( -3.506561 -2.526731 -2.302b8l -2.30256(
E*THEHES
1U
2b) SI
24)
29) 26)
HIGHEST S.202141
5.33971 5.906631 6.39136( 6.4166b(
10 251 26)
291 4) 41
HISSING VALUE COUNI
* COUNT/NtldS
1 9.27
\
4 0112222>v.^ i 7B9
- --
&
BOXPLOI
!*
Cl
8 3
0 u
* 00113 3 5555667709
\
5 10
3 000122223344
\
, 12
? 5555556b7766hti49999.995
22
3 0000000111111)122221(22333333344
31
1 5555SS5bbb666777777'Aa8Hd8a9999999994099
39
1 00000011111 11111222212222233333344 444 4
37
0 5555566666666777777777776666888888949999
43
0 1111122233333333334*4444
24
0 44444443332222111L41000
23
0 9998BB886b87777Tb*6655S
23
-1 43333333332222Lbl111000000
2b
-1 99877766555a5/
-? 333333333332333333333333333333321lOuOOO
-? b -3 -1 55
/
13
39
1
-A
2*5 -0.5*
-2
NORMAL PROBABILITY PLOT
* *
** *** *+
******* *****
il , ,,
-1 0 1 *2
J|0-*v^
--^k-eryCtZu^ nm*i^\ - *?. /
f^ ' s/ ft ~
cn
C
oO
vi
00
I