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Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 14 Dec 2009 16:45:04 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/15/t1260834606wkkg0yi7rjijryr.htm/, Retrieved Wed, 08 May 2024 13:47:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67743, Retrieved Wed, 08 May 2024 13:47:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2009-12-14 23:45:04] [c4328af89eba9af53ee195d6fed304d9] [Current]
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Dataseries X:
353,4
329,08
331,89
339,94
330,8
361,26
358,02
356,15
322,56
306,1
303,99
322,23
330,2
343,91
367,07
375,22
375,35
389,81
371,18
387,18
395,43
387,86
392,46
375,11
417,03
408,79
412,68
403,67
414,95
415,35
408,2
424,19
414,03
417,8
418,66
431,35
435,7
438,78
443,38
451,67
440,19
450,23
450,54
448,13
463,55
458,93
467,83
461,93
466,51
481,6
467,19
445,66
450,91
456,5
444,27
458,28
475,49
462,69
472,26
453,55
459,21
470,42
487,39
500,7
514,76
533,4
544,75
562,06
561,88
584,41
581,5
605,37
615,93
636,02
640,43
645,5
654,17
669,12
670,63
639,95
651,99
687,31
705,27
757,02
740,74
786,16
790,82
757,12
801,34
848,28
885,14
954,29
899,47
947,28
914,62
955,4
970,43
980,28
1049,34
1101,75
1111,75
1090,82
1133,84
1120,67
957,28
1017,01
1098,67
1163,63
1129,23
1279,64
1238,33
1286,37
1335,18
1301,84
1372,71
1328,72
1320,41
1282,71
1362,93
1388,91
1469,25
1394,46
1366,42
1498,58
1452,43
1420,6
1454,6
1430,83
1517,68
1436,52
1429,4
1314,95
1320,28
1366,01
1239,94
1160,33
1249,46
1255,82
1224,42
1211,23
1133,58
1040,94
1059,78
1139,45
1148,08
1130,2
1106,73
1147,39
1076,92
1067,14
989,82
911,62
916,07
815,28
885,76
936,31
879,82
855,7
841,15
848,18
916,92
963,59
974,5
990,31
1008,01
995,97
1050,71
1058,2
1111,92
1131,13
1144,94
1113,89
1107,3
1120,68
1140,84
1101,72
1104,24
1114,58
1130,2
1173,78
1211,92
1181,27
1203,6
1180,59
1156,85
1191,5
1191,33
1234,18
1220,33
1228,81
1207,01
1249,48
1248,29
1280,08
1280,66
1302,88
1310,61
1270,05
1270,06
1278,53
1303,8
1335,83
1377,76
1400,63
1418,03
1437,9
1406,8
1420,83
1482,37
1530,63
1504,66
1455,18
1473,96
1527,29
1545,79
1479,63
1467,97
1378,6
1330,45
1326,41
1385,97
1399,62
1276,69
1269,42
1287,83
1164,17
968,67
888,61
902,99
823,09
729,57
793,59
872,74
923,26
920,82
990,22
1019,52
1054,91
1036,18
1098,89




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67743&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67743&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67743&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1334.61833333333319.551938212841957.27
2374.23166666666719.770292145417465.23
3415.5583333333337.342377412024427.68
4450.90510.40464100992732.13
5461.242511.801778852821737.3300000000000
6533.82083333333347.5383199416932146.16
7664.44537.8727007702958141.09
8856.72166666666779.3597400602109214.66
91066.2891666666769.5147673596094206.35
101302.2483333333369.6996895562845259.68
111432.1433333333355.316140556447202.73
121200.1033333333397.4771055015981325.07
131010.94333333333115.667938775644332.8
14948.58833333333377.952030334901217.05
151124.6016666666720.886476195825672.06
161204.7391666666726.166321677903492.6300000000001
171304.9316666666745.7258500260636152.34
181473.5891666666747.071785499931138.99
191262.03416666667174.546788229004579.36
20930.481666666667113.372113039987369.32

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 334.618333333333 & 19.5519382128419 & 57.27 \tabularnewline
2 & 374.231666666667 & 19.7702921454174 & 65.23 \tabularnewline
3 & 415.558333333333 & 7.3423774120244 & 27.68 \tabularnewline
4 & 450.905 & 10.404641009927 & 32.13 \tabularnewline
5 & 461.2425 & 11.8017788528217 & 37.3300000000000 \tabularnewline
6 & 533.820833333333 & 47.5383199416932 & 146.16 \tabularnewline
7 & 664.445 & 37.8727007702958 & 141.09 \tabularnewline
8 & 856.721666666667 & 79.3597400602109 & 214.66 \tabularnewline
9 & 1066.28916666667 & 69.5147673596094 & 206.35 \tabularnewline
10 & 1302.24833333333 & 69.6996895562845 & 259.68 \tabularnewline
11 & 1432.14333333333 & 55.316140556447 & 202.73 \tabularnewline
12 & 1200.10333333333 & 97.4771055015981 & 325.07 \tabularnewline
13 & 1010.94333333333 & 115.667938775644 & 332.8 \tabularnewline
14 & 948.588333333333 & 77.952030334901 & 217.05 \tabularnewline
15 & 1124.60166666667 & 20.8864761958256 & 72.06 \tabularnewline
16 & 1204.73916666667 & 26.1663216779034 & 92.6300000000001 \tabularnewline
17 & 1304.93166666667 & 45.7258500260636 & 152.34 \tabularnewline
18 & 1473.58916666667 & 47.071785499931 & 138.99 \tabularnewline
19 & 1262.03416666667 & 174.546788229004 & 579.36 \tabularnewline
20 & 930.481666666667 & 113.372113039987 & 369.32 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67743&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]334.618333333333[/C][C]19.5519382128419[/C][C]57.27[/C][/ROW]
[ROW][C]2[/C][C]374.231666666667[/C][C]19.7702921454174[/C][C]65.23[/C][/ROW]
[ROW][C]3[/C][C]415.558333333333[/C][C]7.3423774120244[/C][C]27.68[/C][/ROW]
[ROW][C]4[/C][C]450.905[/C][C]10.404641009927[/C][C]32.13[/C][/ROW]
[ROW][C]5[/C][C]461.2425[/C][C]11.8017788528217[/C][C]37.3300000000000[/C][/ROW]
[ROW][C]6[/C][C]533.820833333333[/C][C]47.5383199416932[/C][C]146.16[/C][/ROW]
[ROW][C]7[/C][C]664.445[/C][C]37.8727007702958[/C][C]141.09[/C][/ROW]
[ROW][C]8[/C][C]856.721666666667[/C][C]79.3597400602109[/C][C]214.66[/C][/ROW]
[ROW][C]9[/C][C]1066.28916666667[/C][C]69.5147673596094[/C][C]206.35[/C][/ROW]
[ROW][C]10[/C][C]1302.24833333333[/C][C]69.6996895562845[/C][C]259.68[/C][/ROW]
[ROW][C]11[/C][C]1432.14333333333[/C][C]55.316140556447[/C][C]202.73[/C][/ROW]
[ROW][C]12[/C][C]1200.10333333333[/C][C]97.4771055015981[/C][C]325.07[/C][/ROW]
[ROW][C]13[/C][C]1010.94333333333[/C][C]115.667938775644[/C][C]332.8[/C][/ROW]
[ROW][C]14[/C][C]948.588333333333[/C][C]77.952030334901[/C][C]217.05[/C][/ROW]
[ROW][C]15[/C][C]1124.60166666667[/C][C]20.8864761958256[/C][C]72.06[/C][/ROW]
[ROW][C]16[/C][C]1204.73916666667[/C][C]26.1663216779034[/C][C]92.6300000000001[/C][/ROW]
[ROW][C]17[/C][C]1304.93166666667[/C][C]45.7258500260636[/C][C]152.34[/C][/ROW]
[ROW][C]18[/C][C]1473.58916666667[/C][C]47.071785499931[/C][C]138.99[/C][/ROW]
[ROW][C]19[/C][C]1262.03416666667[/C][C]174.546788229004[/C][C]579.36[/C][/ROW]
[ROW][C]20[/C][C]930.481666666667[/C][C]113.372113039987[/C][C]369.32[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67743&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67743&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1334.61833333333319.551938212841957.27
2374.23166666666719.770292145417465.23
3415.5583333333337.342377412024427.68
4450.90510.40464100992732.13
5461.242511.801778852821737.3300000000000
6533.82083333333347.5383199416932146.16
7664.44537.8727007702958141.09
8856.72166666666779.3597400602109214.66
91066.2891666666769.5147673596094206.35
101302.2483333333369.6996895562845259.68
111432.1433333333355.316140556447202.73
121200.1033333333397.4771055015981325.07
131010.94333333333115.667938775644332.8
14948.58833333333377.952030334901217.05
151124.6016666666720.886476195825672.06
161204.7391666666726.166321677903492.6300000000001
171304.9316666666745.7258500260636152.34
181473.5891666666747.071785499931138.99
191262.03416666667174.546788229004579.36
20930.481666666667113.372113039987369.32







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.7709870874252
beta0.0562121703281903
S.D.0.0233426013295469
T-STAT2.40813650263723
p-value0.0269723945639571

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.7709870874252 \tabularnewline
beta & 0.0562121703281903 \tabularnewline
S.D. & 0.0233426013295469 \tabularnewline
T-STAT & 2.40813650263723 \tabularnewline
p-value & 0.0269723945639571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67743&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.7709870874252[/C][/ROW]
[ROW][C]beta[/C][C]0.0562121703281903[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0233426013295469[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.40813650263723[/C][/ROW]
[ROW][C]p-value[/C][C]0.0269723945639571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67743&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67743&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.7709870874252
beta0.0562121703281903
S.D.0.0233426013295469
T-STAT2.40813650263723
p-value0.0269723945639571







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.44093605433636
beta1.21670640050691
S.D.0.306732639082211
T-STAT3.96666753217874
p-value0.000904557688208992
Lambda-0.216706400506905

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.44093605433636 \tabularnewline
beta & 1.21670640050691 \tabularnewline
S.D. & 0.306732639082211 \tabularnewline
T-STAT & 3.96666753217874 \tabularnewline
p-value & 0.000904557688208992 \tabularnewline
Lambda & -0.216706400506905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67743&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.44093605433636[/C][/ROW]
[ROW][C]beta[/C][C]1.21670640050691[/C][/ROW]
[ROW][C]S.D.[/C][C]0.306732639082211[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.96666753217874[/C][/ROW]
[ROW][C]p-value[/C][C]0.000904557688208992[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.216706400506905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67743&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67743&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.44093605433636
beta1.21670640050691
S.D.0.306732639082211
T-STAT3.96666753217874
p-value0.000904557688208992
Lambda-0.216706400506905



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')