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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, 08 Dec 2008 05:07:49 -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/2008/Dec/08/t1228738250m9jrtsfbnl4yh94.htm/, Retrieved Thu, 16 May 2024 16:18:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30419, Retrieved Thu, 16 May 2024 16:18:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2008-12-08 12:07:49] [c60a842d48931bd392d024d8e9ef4583] [Current]
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Dataseries X:
0.24
0.23
0.23
0.24
0.23
0.23
0.25
0.21
0.26
0.25
0.24
0.24
0.27
0.25
0.26
0.29
0.24
0.26
0.24
0.26
0.25
0.26
0.24
0.21
0.20
0.22
0.20
0.21
0.20
0.19
0.20
0.20
0.21
0.24
0.22
0.19
0.23
0.23
0.23
0.22
0.23
0.25
0.25
0.22
0.25
0.25
0.24
0.19
0.24
0.26
0.24
0.24
0.25
0.23
0.27
0.24
0.26
0.27
0.29
0.28
0.32
0.29
0.27
0.26
0.28
0.31
0.29
0.31
0.31
0.32
0.32
0.26
0.31
0.31
0.31
0.31
0.29
0.27
0.30
0.27
0.27
0.30
0.28
0.24
0.28
0.28
0.33
0.28
0.29
0.25
0.31
0.29
0.37
0.31
0.29
0.28
0.30
0.32
0.31
0.28
0.29
0.29
0.28
0.26
0.28
0.30
0.33
0.31
0.37
0.36
0.37
0.37
0.36
0.33
0.33
0.40
0.32
0.39
0.39
0.37
0.37
0.30
0.33
0.33
0.34
0.35
0.34
0.37
0.37
0.37
0.36
0.32
0.33
0.35
0.36
0.35
0.37
0.35
0.32
0.33
0.28
0.32
0.35
0.30
0.32
0.32
0.32
0.32
0.36
0.31
0.26
0.33
0.31
0.34
0.33
0.38
0.32
0.30
0.32
0.33
0.34
0.29
0.33
0.36
0.32
0.32
0.32
0.31
0.30
0.34
0.34
0.30
0.28
0.25
0.27
0.33
0.28
0.33
0.32
0.27
0.27
0.28
0.27
0.27
0.25
0.25
0.22
0.27




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=30419&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=30419&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30419&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
10.23750.01288057028664070.05
20.25250.01959823739755460.08
30.2066666666666670.01435481125130550.05
40.23250.01764549903980150.06
50.2558333333333330.01880924981991250.06
60.2950.02315952582337640.06
70.2883333333333330.02249579085208180.07
80.2966666666666670.03055050463303890.12
90.2958333333333330.01975225341958520.07
100.3633333333333330.02534608929251700.08
110.3458333333333330.02314316444667970.07
120.3341666666666670.02609713789020940.09
130.3250.02907670107585360.12
140.3216666666666670.01800673274757040.07
150.3008333333333330.03088345639315460.09

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.2375 & 0.0128805702866407 & 0.05 \tabularnewline
2 & 0.2525 & 0.0195982373975546 & 0.08 \tabularnewline
3 & 0.206666666666667 & 0.0143548112513055 & 0.05 \tabularnewline
4 & 0.2325 & 0.0176454990398015 & 0.06 \tabularnewline
5 & 0.255833333333333 & 0.0188092498199125 & 0.06 \tabularnewline
6 & 0.295 & 0.0231595258233764 & 0.06 \tabularnewline
7 & 0.288333333333333 & 0.0224957908520818 & 0.07 \tabularnewline
8 & 0.296666666666667 & 0.0305505046330389 & 0.12 \tabularnewline
9 & 0.295833333333333 & 0.0197522534195852 & 0.07 \tabularnewline
10 & 0.363333333333333 & 0.0253460892925170 & 0.08 \tabularnewline
11 & 0.345833333333333 & 0.0231431644466797 & 0.07 \tabularnewline
12 & 0.334166666666667 & 0.0260971378902094 & 0.09 \tabularnewline
13 & 0.325 & 0.0290767010758536 & 0.12 \tabularnewline
14 & 0.321666666666667 & 0.0180067327475704 & 0.07 \tabularnewline
15 & 0.300833333333333 & 0.0308834563931546 & 0.09 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30419&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]0.2375[/C][C]0.0128805702866407[/C][C]0.05[/C][/ROW]
[ROW][C]2[/C][C]0.2525[/C][C]0.0195982373975546[/C][C]0.08[/C][/ROW]
[ROW][C]3[/C][C]0.206666666666667[/C][C]0.0143548112513055[/C][C]0.05[/C][/ROW]
[ROW][C]4[/C][C]0.2325[/C][C]0.0176454990398015[/C][C]0.06[/C][/ROW]
[ROW][C]5[/C][C]0.255833333333333[/C][C]0.0188092498199125[/C][C]0.06[/C][/ROW]
[ROW][C]6[/C][C]0.295[/C][C]0.0231595258233764[/C][C]0.06[/C][/ROW]
[ROW][C]7[/C][C]0.288333333333333[/C][C]0.0224957908520818[/C][C]0.07[/C][/ROW]
[ROW][C]8[/C][C]0.296666666666667[/C][C]0.0305505046330389[/C][C]0.12[/C][/ROW]
[ROW][C]9[/C][C]0.295833333333333[/C][C]0.0197522534195852[/C][C]0.07[/C][/ROW]
[ROW][C]10[/C][C]0.363333333333333[/C][C]0.0253460892925170[/C][C]0.08[/C][/ROW]
[ROW][C]11[/C][C]0.345833333333333[/C][C]0.0231431644466797[/C][C]0.07[/C][/ROW]
[ROW][C]12[/C][C]0.334166666666667[/C][C]0.0260971378902094[/C][C]0.09[/C][/ROW]
[ROW][C]13[/C][C]0.325[/C][C]0.0290767010758536[/C][C]0.12[/C][/ROW]
[ROW][C]14[/C][C]0.321666666666667[/C][C]0.0180067327475704[/C][C]0.07[/C][/ROW]
[ROW][C]15[/C][C]0.300833333333333[/C][C]0.0308834563931546[/C][C]0.09[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30419&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30419&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
10.23750.01288057028664070.05
20.25250.01959823739755460.08
30.2066666666666670.01435481125130550.05
40.23250.01764549903980150.06
50.2558333333333330.01880924981991250.06
60.2950.02315952582337640.06
70.2883333333333330.02249579085208180.07
80.2966666666666670.03055050463303890.12
90.2958333333333330.01975225341958520.07
100.3633333333333330.02534608929251700.08
110.3458333333333330.02314316444667970.07
120.3341666666666670.02609713789020940.09
130.3250.02907670107585360.12
140.3216666666666670.01800673274757040.07
150.3008333333333330.03088345639315460.09







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.00153128028640165
beta0.0815248399843677
S.D.0.0255155849398987
T-STAT3.19509978612669
p-value0.00703363102423074

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.00153128028640165 \tabularnewline
beta & 0.0815248399843677 \tabularnewline
S.D. & 0.0255155849398987 \tabularnewline
T-STAT & 3.19509978612669 \tabularnewline
p-value & 0.00703363102423074 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30419&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.00153128028640165[/C][/ROW]
[ROW][C]beta[/C][C]0.0815248399843677[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0255155849398987[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.19509978612669[/C][/ROW]
[ROW][C]p-value[/C][C]0.00703363102423074[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30419&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30419&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-0.00153128028640165
beta0.0815248399843677
S.D.0.0255155849398987
T-STAT3.19509978612669
p-value0.00703363102423074







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.38192515335091
beta1.16873223035786
S.D.0.309814973391639
T-STAT3.77235553712396
p-value0.00232640709285748
Lambda-0.168732230357862

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.38192515335091 \tabularnewline
beta & 1.16873223035786 \tabularnewline
S.D. & 0.309814973391639 \tabularnewline
T-STAT & 3.77235553712396 \tabularnewline
p-value & 0.00232640709285748 \tabularnewline
Lambda & -0.168732230357862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30419&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.38192515335091[/C][/ROW]
[ROW][C]beta[/C][C]1.16873223035786[/C][/ROW]
[ROW][C]S.D.[/C][C]0.309814973391639[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.77235553712396[/C][/ROW]
[ROW][C]p-value[/C][C]0.00232640709285748[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.168732230357862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30419&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30419&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-2.38192515335091
beta1.16873223035786
S.D.0.309814973391639
T-STAT3.77235553712396
p-value0.00232640709285748
Lambda-0.168732230357862



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')