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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 29 Nov 2011 13:46:56 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/29/t1322592577fexc4qcpj4z8v25.htm/, Retrieved Thu, 25 Apr 2024 07:14:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148668, Retrieved Thu, 25 Apr 2024 07:14:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact64
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [gemiddelde consum...] [2011-11-29 18:46:56] [bd8cebb9d7961275d2f6ed94788b7e5f] [Current]
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Dataseries X:
20.98		
20.1		
20.61		
20.27		
20.08		
23.58		
22.31		
22.89		
21.78		
22.19		
22.58		
22.78		
25.06		
25.16		
25.47		
25.34		
24.2		
25.32		
25.57		
25.76		
24.79		
23.14		
22.66		
22.06		
24.26		
23.15		
22.92		
21.43		
21.56		
23.48		
24.35		
24.83		
24.19		
23.58		
23.58		
24.35		
27.18		
25.69		
24.81		
23.26		
23.49		
26.86		
27.12		
27.66		
26.26		
25.51		
24.63		
23.57		
27.63		
25.85		
26.09		
24.47		
24.19		
25.09		
25.26		
25.58		
24.76		
25.02		
24.24		
24.14		
28.69		
26.74		
26.48		
24.45		
23.88		
26.58		
26.23		
28.63		
26.81		
26.56		
26.64		
26.8		
28.37		
27.13		
28.44		
28.62		
27.28		
31.32		
31.26		
31.41		
31.76		
32.72		
32.15		
33.62		
35.97		
33.78		
33.77		
32.75		
32.55		
33.22		
32.88		
31.56		
30.27		
28.65		
27.89		
27.07		
30.8		
28.38		
27.5		
28		
28.02		
29.2		
27.59		
27.22		
27.16		
26.31		
25.67		
26.41		
28.34		
25.43		
23.72		
23.33		
23.8		
27.7		
26.28		
27.51		
27.93		
28.76		
28.65		
29.52		
31.23		
27.9		
27.87		
27.52		
27.59		
31.2		
30.22		
30.62		
31.52		
30.59		
31.42		
31.95		




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

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148668&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148668&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148668&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' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
120.490.3894440481849310.879999999999999
222.2151.515046753954043.5
322.33250.4423705083599791
425.25750.1830072858294630.41
525.21250.6986355750079351.56
623.16251.171505441728722.73
722.941.164330995321632.83
823.5551.442601816164113.27
923.9250.4036913012026240.770000000000003
1025.2351.640254045364113.92
1126.28251.891249586913374.17
1224.99251.158918317512792.69
1326.011.294604186614583.16
1425.030.5957068630347191.39
1524.540.4198412398355680.879999999999999
1626.591.734377890387984.24
1726.331.94636413174244.75
1826.70250.1228481447424690.25
1928.140.6815179136799471.49
2030.31752.025938054334344.13
2132.56250.8077282959015351.86
2234.06751.357261335680543.22
2332.55250.7159783516280371.66
2428.471.36244877579553.2
2528.671.465014220636333.3
2628.00750.8595880796443531.98
2726.38750.6104847800450611.49
2825.2052.280328923642385.01
2926.32251.795594144937363.9
3028.7150.6507687761409581.59
3128.631.741895519254813.71
3229.90751.596524871922353.61
3331.370.5685654462475421.36

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 20.49 & 0.389444048184931 & 0.879999999999999 \tabularnewline
2 & 22.215 & 1.51504675395404 & 3.5 \tabularnewline
3 & 22.3325 & 0.442370508359979 & 1 \tabularnewline
4 & 25.2575 & 0.183007285829463 & 0.41 \tabularnewline
5 & 25.2125 & 0.698635575007935 & 1.56 \tabularnewline
6 & 23.1625 & 1.17150544172872 & 2.73 \tabularnewline
7 & 22.94 & 1.16433099532163 & 2.83 \tabularnewline
8 & 23.555 & 1.44260181616411 & 3.27 \tabularnewline
9 & 23.925 & 0.403691301202624 & 0.770000000000003 \tabularnewline
10 & 25.235 & 1.64025404536411 & 3.92 \tabularnewline
11 & 26.2825 & 1.89124958691337 & 4.17 \tabularnewline
12 & 24.9925 & 1.15891831751279 & 2.69 \tabularnewline
13 & 26.01 & 1.29460418661458 & 3.16 \tabularnewline
14 & 25.03 & 0.595706863034719 & 1.39 \tabularnewline
15 & 24.54 & 0.419841239835568 & 0.879999999999999 \tabularnewline
16 & 26.59 & 1.73437789038798 & 4.24 \tabularnewline
17 & 26.33 & 1.9463641317424 & 4.75 \tabularnewline
18 & 26.7025 & 0.122848144742469 & 0.25 \tabularnewline
19 & 28.14 & 0.681517913679947 & 1.49 \tabularnewline
20 & 30.3175 & 2.02593805433434 & 4.13 \tabularnewline
21 & 32.5625 & 0.807728295901535 & 1.86 \tabularnewline
22 & 34.0675 & 1.35726133568054 & 3.22 \tabularnewline
23 & 32.5525 & 0.715978351628037 & 1.66 \tabularnewline
24 & 28.47 & 1.3624487757955 & 3.2 \tabularnewline
25 & 28.67 & 1.46501422063633 & 3.3 \tabularnewline
26 & 28.0075 & 0.859588079644353 & 1.98 \tabularnewline
27 & 26.3875 & 0.610484780045061 & 1.49 \tabularnewline
28 & 25.205 & 2.28032892364238 & 5.01 \tabularnewline
29 & 26.3225 & 1.79559414493736 & 3.9 \tabularnewline
30 & 28.715 & 0.650768776140958 & 1.59 \tabularnewline
31 & 28.63 & 1.74189551925481 & 3.71 \tabularnewline
32 & 29.9075 & 1.59652487192235 & 3.61 \tabularnewline
33 & 31.37 & 0.568565446247542 & 1.36 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148668&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]20.49[/C][C]0.389444048184931[/C][C]0.879999999999999[/C][/ROW]
[ROW][C]2[/C][C]22.215[/C][C]1.51504675395404[/C][C]3.5[/C][/ROW]
[ROW][C]3[/C][C]22.3325[/C][C]0.442370508359979[/C][C]1[/C][/ROW]
[ROW][C]4[/C][C]25.2575[/C][C]0.183007285829463[/C][C]0.41[/C][/ROW]
[ROW][C]5[/C][C]25.2125[/C][C]0.698635575007935[/C][C]1.56[/C][/ROW]
[ROW][C]6[/C][C]23.1625[/C][C]1.17150544172872[/C][C]2.73[/C][/ROW]
[ROW][C]7[/C][C]22.94[/C][C]1.16433099532163[/C][C]2.83[/C][/ROW]
[ROW][C]8[/C][C]23.555[/C][C]1.44260181616411[/C][C]3.27[/C][/ROW]
[ROW][C]9[/C][C]23.925[/C][C]0.403691301202624[/C][C]0.770000000000003[/C][/ROW]
[ROW][C]10[/C][C]25.235[/C][C]1.64025404536411[/C][C]3.92[/C][/ROW]
[ROW][C]11[/C][C]26.2825[/C][C]1.89124958691337[/C][C]4.17[/C][/ROW]
[ROW][C]12[/C][C]24.9925[/C][C]1.15891831751279[/C][C]2.69[/C][/ROW]
[ROW][C]13[/C][C]26.01[/C][C]1.29460418661458[/C][C]3.16[/C][/ROW]
[ROW][C]14[/C][C]25.03[/C][C]0.595706863034719[/C][C]1.39[/C][/ROW]
[ROW][C]15[/C][C]24.54[/C][C]0.419841239835568[/C][C]0.879999999999999[/C][/ROW]
[ROW][C]16[/C][C]26.59[/C][C]1.73437789038798[/C][C]4.24[/C][/ROW]
[ROW][C]17[/C][C]26.33[/C][C]1.9463641317424[/C][C]4.75[/C][/ROW]
[ROW][C]18[/C][C]26.7025[/C][C]0.122848144742469[/C][C]0.25[/C][/ROW]
[ROW][C]19[/C][C]28.14[/C][C]0.681517913679947[/C][C]1.49[/C][/ROW]
[ROW][C]20[/C][C]30.3175[/C][C]2.02593805433434[/C][C]4.13[/C][/ROW]
[ROW][C]21[/C][C]32.5625[/C][C]0.807728295901535[/C][C]1.86[/C][/ROW]
[ROW][C]22[/C][C]34.0675[/C][C]1.35726133568054[/C][C]3.22[/C][/ROW]
[ROW][C]23[/C][C]32.5525[/C][C]0.715978351628037[/C][C]1.66[/C][/ROW]
[ROW][C]24[/C][C]28.47[/C][C]1.3624487757955[/C][C]3.2[/C][/ROW]
[ROW][C]25[/C][C]28.67[/C][C]1.46501422063633[/C][C]3.3[/C][/ROW]
[ROW][C]26[/C][C]28.0075[/C][C]0.859588079644353[/C][C]1.98[/C][/ROW]
[ROW][C]27[/C][C]26.3875[/C][C]0.610484780045061[/C][C]1.49[/C][/ROW]
[ROW][C]28[/C][C]25.205[/C][C]2.28032892364238[/C][C]5.01[/C][/ROW]
[ROW][C]29[/C][C]26.3225[/C][C]1.79559414493736[/C][C]3.9[/C][/ROW]
[ROW][C]30[/C][C]28.715[/C][C]0.650768776140958[/C][C]1.59[/C][/ROW]
[ROW][C]31[/C][C]28.63[/C][C]1.74189551925481[/C][C]3.71[/C][/ROW]
[ROW][C]32[/C][C]29.9075[/C][C]1.59652487192235[/C][C]3.61[/C][/ROW]
[ROW][C]33[/C][C]31.37[/C][C]0.568565446247542[/C][C]1.36[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148668&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148668&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
120.490.3894440481849310.879999999999999
222.2151.515046753954043.5
322.33250.4423705083599791
425.25750.1830072858294630.41
525.21250.6986355750079351.56
623.16251.171505441728722.73
722.941.164330995321632.83
823.5551.442601816164113.27
923.9250.4036913012026240.770000000000003
1025.2351.640254045364113.92
1126.28251.891249586913374.17
1224.99251.158918317512792.69
1326.011.294604186614583.16
1425.030.5957068630347191.39
1524.540.4198412398355680.879999999999999
1626.591.734377890387984.24
1726.331.94636413174244.75
1826.70250.1228481447424690.25
1928.140.6815179136799471.49
2030.31752.025938054334344.13
2132.56250.8077282959015351.86
2234.06751.357261335680543.22
2332.55250.7159783516280371.66
2428.471.36244877579553.2
2528.671.465014220636333.3
2628.00750.8595880796443531.98
2726.38750.6104847800450611.49
2825.2052.280328923642385.01
2926.32251.795594144937363.9
3028.7150.6507687761409581.59
3128.631.741895519254813.71
3229.90751.596524871922353.61
3331.370.5685654462475421.36







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.512283582989553
beta0.022529778222743
S.D.0.0330802049519014
T-STAT0.681065255052115
p-value0.500886403360081

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.512283582989553 \tabularnewline
beta & 0.022529778222743 \tabularnewline
S.D. & 0.0330802049519014 \tabularnewline
T-STAT & 0.681065255052115 \tabularnewline
p-value & 0.500886403360081 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148668&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.512283582989553[/C][/ROW]
[ROW][C]beta[/C][C]0.022529778222743[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0330802049519014[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.681065255052115[/C][/ROW]
[ROW][C]p-value[/C][C]0.500886403360081[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148668&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148668&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)
alpha0.512283582989553
beta0.022529778222743
S.D.0.0330802049519014
T-STAT0.681065255052115
p-value0.500886403360081







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.37948189913581
beta1.00554169178509
S.D.1.04858623661165
T-STAT0.958949923884514
p-value0.345003902924398
Lambda-0.00554169178508901

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.37948189913581 \tabularnewline
beta & 1.00554169178509 \tabularnewline
S.D. & 1.04858623661165 \tabularnewline
T-STAT & 0.958949923884514 \tabularnewline
p-value & 0.345003902924398 \tabularnewline
Lambda & -0.00554169178508901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148668&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.37948189913581[/C][/ROW]
[ROW][C]beta[/C][C]1.00554169178509[/C][/ROW]
[ROW][C]S.D.[/C][C]1.04858623661165[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.958949923884514[/C][/ROW]
[ROW][C]p-value[/C][C]0.345003902924398[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.00554169178508901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148668&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148668&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-3.37948189913581
beta1.00554169178509
S.D.1.04858623661165
T-STAT0.958949923884514
p-value0.345003902924398
Lambda-0.00554169178508901



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')