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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, 28 Nov 2007 08:00:51 -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/Nov/28/t1196261439k5uxret6kfhc0sv.htm/, Retrieved Wed, 01 May 2024 23:57:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7075, Retrieved Wed, 01 May 2024 23:57:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Q1 Tijdreeks 2] [2007-11-28 15:00:51] [0c269222ff5238ed17e011dfedaec76b] [Current]
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Dataseries X:
544.5
619.8
777.6
640.4
633.0
722.0
860.1
495.1
692.8
766.7
648.5
640.0
681.6
752.5
1031.7
685.5
887.6
655.4
944.2
626.6
1221.8
939.6
886.6
811.3
774.7
910.6
911.6
697.7
829.8
824.3
885.6
538.9
686.0
878.7
812.7
640.4
773.9
795.9
836.3
876.1
851.7
692.4
877.3
536.8
705.9
951.0
755.7
695.5
744.8
672.1
666.6
760.8
756.0
604.4
883.9
527.9
756.2
812.9
655.6
707.6




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=7075&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=7075&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7075&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
1670.041666666667101.245960263593315.6
2843.7177.002424225823602
3782.583333333333118.304098394644245
4779.041666666667111.42654701097310.6
5712.495.059541149936250.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 670.041666666667 & 101.245960263593 & 315.6 \tabularnewline
2 & 843.7 & 177.002424225823 & 602 \tabularnewline
3 & 782.583333333333 & 118.304098394644 & 245 \tabularnewline
4 & 779.041666666667 & 111.42654701097 & 310.6 \tabularnewline
5 & 712.4 & 95.059541149936 & 250.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7075&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]670.041666666667[/C][C]101.245960263593[/C][C]315.6[/C][/ROW]
[ROW][C]2[/C][C]843.7[/C][C]177.002424225823[/C][C]602[/C][/ROW]
[ROW][C]3[/C][C]782.583333333333[/C][C]118.304098394644[/C][C]245[/C][/ROW]
[ROW][C]4[/C][C]779.041666666667[/C][C]111.42654701097[/C][C]310.6[/C][/ROW]
[ROW][C]5[/C][C]712.4[/C][C]95.059541149936[/C][C]250.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7075&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7075&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
1670.041666666667101.245960263593315.6
2843.7177.002424225823602
3782.583333333333118.304098394644245
4779.041666666667111.42654701097310.6
5712.495.059541149936250.9







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-189.428352975994
beta0.409259722771977
S.D.0.151162010629679
T-STAT2.70742444525028
p-value0.0733239389749198

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -189.428352975994 \tabularnewline
beta & 0.409259722771977 \tabularnewline
S.D. & 0.151162010629679 \tabularnewline
T-STAT & 2.70742444525028 \tabularnewline
p-value & 0.0733239389749198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7075&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-189.428352975994[/C][/ROW]
[ROW][C]beta[/C][C]0.409259722771977[/C][/ROW]
[ROW][C]S.D.[/C][C]0.151162010629679[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.70742444525028[/C][/ROW]
[ROW][C]p-value[/C][C]0.0733239389749198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7075&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7075&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-189.428352975994
beta0.409259722771977
S.D.0.151162010629679
T-STAT2.70742444525028
p-value0.0733239389749198







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-10.4830128509041
beta2.30122811136772
S.D.0.833175494870187
T-STAT2.76199687285121
p-value0.0700352503496486
Lambda-1.30122811136772

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.4830128509041 \tabularnewline
beta & 2.30122811136772 \tabularnewline
S.D. & 0.833175494870187 \tabularnewline
T-STAT & 2.76199687285121 \tabularnewline
p-value & 0.0700352503496486 \tabularnewline
Lambda & -1.30122811136772 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7075&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.4830128509041[/C][/ROW]
[ROW][C]beta[/C][C]2.30122811136772[/C][/ROW]
[ROW][C]S.D.[/C][C]0.833175494870187[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.76199687285121[/C][/ROW]
[ROW][C]p-value[/C][C]0.0700352503496486[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.30122811136772[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7075&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7075&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-10.4830128509041
beta2.30122811136772
S.D.0.833175494870187
T-STAT2.76199687285121
p-value0.0700352503496486
Lambda-1.30122811136772



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')