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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, 22 Dec 2009 13:30:19 -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/22/t1261513911h4h72cdm3obn6c3.htm/, Retrieved Sat, 04 May 2024 06:31:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70481, Retrieved Sat, 04 May 2024 06:31:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard Daviatio...] [2009-12-22 20:30:19] [a00bf033610db033bc2faa6c748d42a9] [Current]
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Dataseries X:
76,3
71
85,9
109
83,4
101,3
81,6
84,8
88
88,4
85,2
139,5
85,3
79,4
131
91,4
88,2
113,2
81,9
89
95,7
93,2
98
140,5
93
82,1
86,3
84,8
85,7
110,8
87,4
100,4
100,4
99,4
108
161,7
109,3
99,9
110,3
97,5
102,4
122,3
104,4
122,7
127,3
128,4
125,3
187,1
131,4
125,6
142,9
116,6
129,7
155,4
138,7
167,7
155,8
157,1
159,9
244,6
154,3
143,2
147,3
155,1
152,2
166,5
161,2
180,1
169,2
164,5
166,2
267,3




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=70481&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=70481&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70481&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
185.5516.805653810548438
287.7759.111302504764819.7
3100.27526.188722127409554.3
496.77523.336719992321151.6
593.07513.787282787651331.3
6106.8522.518806954780447.3
786.554.6378874501220910.9
896.07511.809988710127325.1
9117.37529.798475911809162.3
10104.256.4958961403848412.8
11112.9511.058782332005020.3
12142.02530.077386300452861.8
13129.12511.018582788483626.3
14147.87516.972207674116338
15179.3543.533626849444488.8
16149.9755.7162779265299411.9
1716511.669618674147027.9
18191.850.3708248890169102.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 85.55 & 16.8056538105484 & 38 \tabularnewline
2 & 87.775 & 9.1113025047648 & 19.7 \tabularnewline
3 & 100.275 & 26.1887221274095 & 54.3 \tabularnewline
4 & 96.775 & 23.3367199923211 & 51.6 \tabularnewline
5 & 93.075 & 13.7872827876513 & 31.3 \tabularnewline
6 & 106.85 & 22.5188069547804 & 47.3 \tabularnewline
7 & 86.55 & 4.63788745012209 & 10.9 \tabularnewline
8 & 96.075 & 11.8099887101273 & 25.1 \tabularnewline
9 & 117.375 & 29.7984759118091 & 62.3 \tabularnewline
10 & 104.25 & 6.49589614038484 & 12.8 \tabularnewline
11 & 112.95 & 11.0587823320050 & 20.3 \tabularnewline
12 & 142.025 & 30.0773863004528 & 61.8 \tabularnewline
13 & 129.125 & 11.0185827884836 & 26.3 \tabularnewline
14 & 147.875 & 16.9722076741163 & 38 \tabularnewline
15 & 179.35 & 43.5336268494444 & 88.8 \tabularnewline
16 & 149.975 & 5.71627792652994 & 11.9 \tabularnewline
17 & 165 & 11.6696186741470 & 27.9 \tabularnewline
18 & 191.8 & 50.3708248890169 & 102.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70481&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]85.55[/C][C]16.8056538105484[/C][C]38[/C][/ROW]
[ROW][C]2[/C][C]87.775[/C][C]9.1113025047648[/C][C]19.7[/C][/ROW]
[ROW][C]3[/C][C]100.275[/C][C]26.1887221274095[/C][C]54.3[/C][/ROW]
[ROW][C]4[/C][C]96.775[/C][C]23.3367199923211[/C][C]51.6[/C][/ROW]
[ROW][C]5[/C][C]93.075[/C][C]13.7872827876513[/C][C]31.3[/C][/ROW]
[ROW][C]6[/C][C]106.85[/C][C]22.5188069547804[/C][C]47.3[/C][/ROW]
[ROW][C]7[/C][C]86.55[/C][C]4.63788745012209[/C][C]10.9[/C][/ROW]
[ROW][C]8[/C][C]96.075[/C][C]11.8099887101273[/C][C]25.1[/C][/ROW]
[ROW][C]9[/C][C]117.375[/C][C]29.7984759118091[/C][C]62.3[/C][/ROW]
[ROW][C]10[/C][C]104.25[/C][C]6.49589614038484[/C][C]12.8[/C][/ROW]
[ROW][C]11[/C][C]112.95[/C][C]11.0587823320050[/C][C]20.3[/C][/ROW]
[ROW][C]12[/C][C]142.025[/C][C]30.0773863004528[/C][C]61.8[/C][/ROW]
[ROW][C]13[/C][C]129.125[/C][C]11.0185827884836[/C][C]26.3[/C][/ROW]
[ROW][C]14[/C][C]147.875[/C][C]16.9722076741163[/C][C]38[/C][/ROW]
[ROW][C]15[/C][C]179.35[/C][C]43.5336268494444[/C][C]88.8[/C][/ROW]
[ROW][C]16[/C][C]149.975[/C][C]5.71627792652994[/C][C]11.9[/C][/ROW]
[ROW][C]17[/C][C]165[/C][C]11.6696186741470[/C][C]27.9[/C][/ROW]
[ROW][C]18[/C][C]191.8[/C][C]50.3708248890169[/C][C]102.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70481&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70481&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
185.5516.805653810548438
287.7759.111302504764819.7
3100.27526.188722127409554.3
496.77523.336719992321151.6
593.07513.787282787651331.3
6106.8522.518806954780447.3
786.554.6378874501220910.9
896.07511.809988710127325.1
9117.37529.798475911809162.3
10104.256.4958961403848412.8
11112.9511.058782332005020.3
12142.02530.077386300452861.8
13129.12511.018582788483626.3
14147.87516.972207674116338
15179.3543.533626849444488.8
16149.9755.7162779265299411.9
1716511.669618674147027.9
18191.850.3708248890169102.8







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-7.93957909645246
beta0.222479861154429
S.D.0.0786842138037763
T-STAT2.82750313435491
p-value0.0121324835229344

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -7.93957909645246 \tabularnewline
beta & 0.222479861154429 \tabularnewline
S.D. & 0.0786842138037763 \tabularnewline
T-STAT & 2.82750313435491 \tabularnewline
p-value & 0.0121324835229344 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70481&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.93957909645246[/C][/ROW]
[ROW][C]beta[/C][C]0.222479861154429[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0786842138037763[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.82750313435491[/C][/ROW]
[ROW][C]p-value[/C][C]0.0121324835229344[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70481&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70481&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)
alpha-7.93957909645246
beta0.222479861154429
S.D.0.0786842138037763
T-STAT2.82750313435491
p-value0.0121324835229344







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.58180360771296
beta1.11657701889495
S.D.0.587574621254113
T-STAT1.90031525955247
p-value0.075565216543478
Lambda-0.116577018894952

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.58180360771296 \tabularnewline
beta & 1.11657701889495 \tabularnewline
S.D. & 0.587574621254113 \tabularnewline
T-STAT & 1.90031525955247 \tabularnewline
p-value & 0.075565216543478 \tabularnewline
Lambda & -0.116577018894952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70481&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.58180360771296[/C][/ROW]
[ROW][C]beta[/C][C]1.11657701889495[/C][/ROW]
[ROW][C]S.D.[/C][C]0.587574621254113[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.90031525955247[/C][/ROW]
[ROW][C]p-value[/C][C]0.075565216543478[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.116577018894952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70481&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70481&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-2.58180360771296
beta1.11657701889495
S.D.0.587574621254113
T-STAT1.90031525955247
p-value0.075565216543478
Lambda-0.116577018894952



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')