Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 10 Dec 2007 07:56:04 -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/2007/Dec/10/t1197298271iz82k73knvqh92k.htm/, Retrieved Mon, 06 May 2024 23:24:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2986, Retrieved Mon, 06 May 2024 23:24:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact232
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Paper VII Stddevmnpl] [2007-12-10 14:56:04] [fd802f308f037a9692de8c23f8b60e49] [Current]
Feedback Forum

Post a new message
Dataseries X:
0.4
0.37
0.36
0.36
0.36
0.36
0.32
0.31
0.32
0.33
0.33
0.29
0.33
0.32
0.31
0.33
0.32
0.32
0.3
0.3
0.33
0.35
0.35
0.37
0.38
0.39
0.4
0.32
0.29
0.29
0.3
0.3
0.32
0.32
0.34
0.34
0.34
0.33
0.33
0.33
0.34
0.35
0.34
0.36
0.39
0.43
0.42
0.39
0.37
0.36
0.39
0.39
0.37
0.36
0.38
0.38
0.44
0.49
0.47
0.48




Summary of compuational 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 compuational 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=2986&T=0

[TABLE]
[ROW][C]Summary of compuational 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=2986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2986&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 compuational 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
10.34250.03078517943308550.07
20.32750.02094364733365140.05
30.33250.03864171085992210.09
40.36250.03596083728421540.11
50.4066666666666670.04905161165609760.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.3425 & 0.0307851794330855 & 0.07 \tabularnewline
2 & 0.3275 & 0.0209436473336514 & 0.05 \tabularnewline
3 & 0.3325 & 0.0386417108599221 & 0.09 \tabularnewline
4 & 0.3625 & 0.0359608372842154 & 0.11 \tabularnewline
5 & 0.406666666666667 & 0.0490516116560976 & 0.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2986&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]0.3425[/C][C]0.0307851794330855[/C][C]0.07[/C][/ROW]
[ROW][C]2[/C][C]0.3275[/C][C]0.0209436473336514[/C][C]0.05[/C][/ROW]
[ROW][C]3[/C][C]0.3325[/C][C]0.0386417108599221[/C][C]0.09[/C][/ROW]
[ROW][C]4[/C][C]0.3625[/C][C]0.0359608372842154[/C][C]0.11[/C][/ROW]
[ROW][C]5[/C][C]0.406666666666667[/C][C]0.0490516116560976[/C][C]0.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2986&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
10.34250.03078517943308550.07
20.32750.02094364733365140.05
30.33250.03864171085992210.09
40.36250.03596083728421540.11
50.4066666666666670.04905161165609760.2







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0582288550479975
beta0.263326770540147
S.D.0.106037069499425
T-STAT2.48334635975182
p-value0.0890060269019799

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0582288550479975 \tabularnewline
beta & 0.263326770540147 \tabularnewline
S.D. & 0.106037069499425 \tabularnewline
T-STAT & 2.48334635975182 \tabularnewline
p-value & 0.0890060269019799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2986&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0582288550479975[/C][/ROW]
[ROW][C]beta[/C][C]0.263326770540147[/C][/ROW]
[ROW][C]S.D.[/C][C]0.106037069499425[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.48334635975182[/C][/ROW]
[ROW][C]p-value[/C][C]0.0890060269019799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2986&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2986&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-0.0582288550479975
beta0.263326770540147
S.D.0.106037069499425
T-STAT2.48334635975182
p-value0.0890060269019799







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.518571879144159
beta2.757336905412
S.D.1.33020033231014
T-STAT2.07287341495651
p-value0.129884534691343
Lambda-1.75733690541200

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.518571879144159 \tabularnewline
beta & 2.757336905412 \tabularnewline
S.D. & 1.33020033231014 \tabularnewline
T-STAT & 2.07287341495651 \tabularnewline
p-value & 0.129884534691343 \tabularnewline
Lambda & -1.75733690541200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2986&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.518571879144159[/C][/ROW]
[ROW][C]beta[/C][C]2.757336905412[/C][/ROW]
[ROW][C]S.D.[/C][C]1.33020033231014[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.07287341495651[/C][/ROW]
[ROW][C]p-value[/C][C]0.129884534691343[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.75733690541200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2986&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2986&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-0.518571879144159
beta2.757336905412
S.D.1.33020033231014
T-STAT2.07287341495651
p-value0.129884534691343
Lambda-1.75733690541200



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')