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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 04 Dec 2013 15:43:03 -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/04/t1386189794527vstly07zqaef.htm/, Retrieved Thu, 28 Mar 2024 08:26:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230812, Retrieved Thu, 28 Mar 2024 08:26:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-04 20:43:03] [c3373c0d5a698012d591c0e2feefe9b5] [Current]
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Dataseries X:
2.57
2.58
2.58
2.58
2.57
2.57
2.57
2.57
2.59
2.62
2.66
2.67
2.67
2.69
2.69
2.69
2.69
2.71
2.71
2.71
2.74
2.77
2.82
2.82
2.82
2.8
2.82
2.82
2.82
2.82
2.82
2.82
2.85
2.93
2.94
2.94
2.95
2.95
2.96
2.96
2.97
2.97
2.97
2.97
2.98
3.03
3.03
3.03
3.03
3.04
3.05
3.06
3.06
3.07
3.07
3.07
3.04
3.06
3.09
3.09
3.09
3.09
3.1
3.1
3.1
3.1
3.1
3.11
3.11
3.17
3.19
3.19
3.19
3.19
3.19
3.19
3.19
3.19
3.19
3.19
3.25
3.23
3.24
3.24




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230812&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230812&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230812&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12.594166666666670.03604500553811070.1
22.725833333333330.05124953806148060.15
32.850.05342794638150960.14
42.980833333333330.03088345639315440.0799999999999996
53.060833333333330.01880924981991250.0600000000000001
63.120833333333330.03848455022552040.1
73.206666666666670.02498484389069560.0600000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.59416666666667 & 0.0360450055381107 & 0.1 \tabularnewline
2 & 2.72583333333333 & 0.0512495380614806 & 0.15 \tabularnewline
3 & 2.85 & 0.0534279463815096 & 0.14 \tabularnewline
4 & 2.98083333333333 & 0.0308834563931544 & 0.0799999999999996 \tabularnewline
5 & 3.06083333333333 & 0.0188092498199125 & 0.0600000000000001 \tabularnewline
6 & 3.12083333333333 & 0.0384845502255204 & 0.1 \tabularnewline
7 & 3.20666666666667 & 0.0249848438906956 & 0.0600000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230812&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]2.59416666666667[/C][C]0.0360450055381107[/C][C]0.1[/C][/ROW]
[ROW][C]2[/C][C]2.72583333333333[/C][C]0.0512495380614806[/C][C]0.15[/C][/ROW]
[ROW][C]3[/C][C]2.85[/C][C]0.0534279463815096[/C][C]0.14[/C][/ROW]
[ROW][C]4[/C][C]2.98083333333333[/C][C]0.0308834563931544[/C][C]0.0799999999999996[/C][/ROW]
[ROW][C]5[/C][C]3.06083333333333[/C][C]0.0188092498199125[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]6[/C][C]3.12083333333333[/C][C]0.0384845502255204[/C][C]0.1[/C][/ROW]
[ROW][C]7[/C][C]3.20666666666667[/C][C]0.0249848438906956[/C][C]0.0600000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230812&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230812&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
12.594166666666670.03604500553811070.1
22.725833333333330.05124953806148060.15
32.850.05342794638150960.14
42.980833333333330.03088345639315440.0799999999999996
53.060833333333330.01880924981991250.0600000000000001
63.120833333333330.03848455022552040.1
73.206666666666670.02498484389069560.0600000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.132404057677049
beta-0.0327639297324118
S.D.0.02137077656188
T-STAT-1.5331183514807
p-value0.185823753670866

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.132404057677049 \tabularnewline
beta & -0.0327639297324118 \tabularnewline
S.D. & 0.02137077656188 \tabularnewline
T-STAT & -1.5331183514807 \tabularnewline
p-value & 0.185823753670866 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230812&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.132404057677049[/C][/ROW]
[ROW][C]beta[/C][C]-0.0327639297324118[/C][/ROW]
[ROW][C]S.D.[/C][C]0.02137077656188[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.5331183514807[/C][/ROW]
[ROW][C]p-value[/C][C]0.185823753670866[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230812&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230812&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)
alpha0.132404057677049
beta-0.0327639297324118
S.D.0.02137077656188
T-STAT-1.5331183514807
p-value0.185823753670866







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.417460792814016
beta-2.75343328807986
S.D.1.81649682119021
T-STAT-1.51579306716086
p-value0.190009011951331
Lambda3.75343328807986

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.417460792814016 \tabularnewline
beta & -2.75343328807986 \tabularnewline
S.D. & 1.81649682119021 \tabularnewline
T-STAT & -1.51579306716086 \tabularnewline
p-value & 0.190009011951331 \tabularnewline
Lambda & 3.75343328807986 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230812&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.417460792814016[/C][/ROW]
[ROW][C]beta[/C][C]-2.75343328807986[/C][/ROW]
[ROW][C]S.D.[/C][C]1.81649682119021[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.51579306716086[/C][/ROW]
[ROW][C]p-value[/C][C]0.190009011951331[/C][/ROW]
[ROW][C]Lambda[/C][C]3.75343328807986[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230812&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230812&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-0.417460792814016
beta-2.75343328807986
S.D.1.81649682119021
T-STAT-1.51579306716086
p-value0.190009011951331
Lambda3.75343328807986



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')