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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 22 Dec 2013 13:14:30 -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/2013/Dec/22/t13877362038uk9sp121krh26v.htm/, Retrieved Sun, 05 Dec 2021 17:47:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232558, Retrieved Sun, 05 Dec 2021 17:47:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact47
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-22 18:14:30] [2bef26084a4a59f589de449f00add791] [Current]
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Dataseries X:
1,49
1,55
1,57
1,6
1,61
1,68
1,72
1,72
1,73
1,74
1,74
1,75
1,75
1,75
1,75
1,76
1,76
1,77
1,78
1,78
1,78
1,78
1,78
1,79
1,79
1,79
1,79
1,79
1,79
1,8
1,8
1,8
1,8
1,8
1,81
1,81
1,82
1,82
1,82
1,82
1,83
1,83
1,84
1,84
1,84
1,85
1,85
1,85
1,86
1,86
1,86
1,86
1,87
1,87
1,87
1,87
1,88
1,9
1,9
1,91
1,91
1,91
1,92
1,92
1,92
1,92
1,92
1,92
1,92
1,92
1,93
1,93
1,93
1,94
1,95
1,95
1,95
1,95
1,98
1,98
2,01
2,02
2,11
2,14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232558&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232558&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232558&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.658333333333330.08973023543664170.26
21.769166666666670.01443375672974070.04
31.79750.00753778361444410.02
41.834166666666670.01240112409372150.03
51.875833333333330.01781640374554410.0499999999999998
61.920.006030226891555280.02
71.99250.06797392548216230.21

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.65833333333333 & 0.0897302354366417 & 0.26 \tabularnewline
2 & 1.76916666666667 & 0.0144337567297407 & 0.04 \tabularnewline
3 & 1.7975 & 0.0075377836144441 & 0.02 \tabularnewline
4 & 1.83416666666667 & 0.0124011240937215 & 0.03 \tabularnewline
5 & 1.87583333333333 & 0.0178164037455441 & 0.0499999999999998 \tabularnewline
6 & 1.92 & 0.00603022689155528 & 0.02 \tabularnewline
7 & 1.9925 & 0.0679739254821623 & 0.21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232558&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]1.65833333333333[/C][C]0.0897302354366417[/C][C]0.26[/C][/ROW]
[ROW][C]2[/C][C]1.76916666666667[/C][C]0.0144337567297407[/C][C]0.04[/C][/ROW]
[ROW][C]3[/C][C]1.7975[/C][C]0.0075377836144441[/C][C]0.02[/C][/ROW]
[ROW][C]4[/C][C]1.83416666666667[/C][C]0.0124011240937215[/C][C]0.03[/C][/ROW]
[ROW][C]5[/C][C]1.87583333333333[/C][C]0.0178164037455441[/C][C]0.0499999999999998[/C][/ROW]
[ROW][C]6[/C][C]1.92[/C][C]0.00603022689155528[/C][C]0.02[/C][/ROW]
[ROW][C]7[/C][C]1.9925[/C][C]0.0679739254821623[/C][C]0.21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232558&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232558&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
11.658333333333330.08973023543664170.26
21.769166666666670.01443375672974070.04
31.79750.00753778361444410.02
41.834166666666670.01240112409372150.03
51.875833333333330.01781640374554410.0499999999999998
61.920.006030226891555280.02
71.99250.06797392548216230.21







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.16662703516193
beta-0.0739806024627127
S.D.0.134576156600294
T-STAT-0.549730385616847
p-value0.606156400908637

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.16662703516193 \tabularnewline
beta & -0.0739806024627127 \tabularnewline
S.D. & 0.134576156600294 \tabularnewline
T-STAT & -0.549730385616847 \tabularnewline
p-value & 0.606156400908637 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232558&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.16662703516193[/C][/ROW]
[ROW][C]beta[/C][C]-0.0739806024627127[/C][/ROW]
[ROW][C]S.D.[/C][C]0.134576156600294[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.549730385616847[/C][/ROW]
[ROW][C]p-value[/C][C]0.606156400908637[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232558&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232558&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)
alpha0.16662703516193
beta-0.0739806024627127
S.D.0.134576156600294
T-STAT-0.549730385616847
p-value0.606156400908637







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.7976338387989
beta-3.57793704752634
S.D.7.62484594415746
T-STAT-0.469247126267245
p-value0.658642657806912
Lambda4.57793704752634

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.7976338387989 \tabularnewline
beta & -3.57793704752634 \tabularnewline
S.D. & 7.62484594415746 \tabularnewline
T-STAT & -0.469247126267245 \tabularnewline
p-value & 0.658642657806912 \tabularnewline
Lambda & 4.57793704752634 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232558&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.7976338387989[/C][/ROW]
[ROW][C]beta[/C][C]-3.57793704752634[/C][/ROW]
[ROW][C]S.D.[/C][C]7.62484594415746[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.469247126267245[/C][/ROW]
[ROW][C]p-value[/C][C]0.658642657806912[/C][/ROW]
[ROW][C]Lambda[/C][C]4.57793704752634[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232558&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232558&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-1.7976338387989
beta-3.57793704752634
S.D.7.62484594415746
T-STAT-0.469247126267245
p-value0.658642657806912
Lambda4.57793704752634



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')