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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 13 Dec 2007 01:12:10 -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/13/t1197532874qc5gxk7zkpgtdev.htm/, Retrieved Sun, 05 May 2024 17:55:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3292, Retrieved Sun, 05 May 2024 17:55:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact238
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Paper bepalen lam...] [2007-12-13 08:12:10] [cb172450b25aceeff04d58e88e905157] [Current]
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Dataseries X:
3,411
3,412
3,594
3,494
3,637
3,542
3,422
3,361
3,202
3,177
2,988
2,804
2,715
2,458
2,435
2,457
2,205
2,091
2,104
2,195
2,109
2,213
2,239
2,168
2,137
2,044
1,936
2,106
2,142
2,195
2,201
2,166
2,212
2,196
2,21
2,215
2,183
2,195
2,207
2,15
2,138
2,097
2,146
2,156
2,209
2,378
2,597
2,637
2,698
2,783
2,985
3,032
3,09
3,245
3,333
3,445
3,567
3,704
3,742
3,853




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=3292&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=3292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3292&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
13.3370.2506972096156851.5
22.282416666666670.1915712344763370.671
32.146666666666670.08406418903901880.279
42.257750.1815314272816390.531
53.289750.3819088718053521.715

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3.337 & 0.250697209615685 & 1.5 \tabularnewline
2 & 2.28241666666667 & 0.191571234476337 & 0.671 \tabularnewline
3 & 2.14666666666667 & 0.0840641890390188 & 0.279 \tabularnewline
4 & 2.25775 & 0.181531427281639 & 0.531 \tabularnewline
5 & 3.28975 & 0.381908871805352 & 1.715 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3292&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]3.337[/C][C]0.250697209615685[/C][C]1.5[/C][/ROW]
[ROW][C]2[/C][C]2.28241666666667[/C][C]0.191571234476337[/C][C]0.671[/C][/ROW]
[ROW][C]3[/C][C]2.14666666666667[/C][C]0.0840641890390188[/C][C]0.279[/C][/ROW]
[ROW][C]4[/C][C]2.25775[/C][C]0.181531427281639[/C][C]0.531[/C][/ROW]
[ROW][C]5[/C][C]3.28975[/C][C]0.381908871805352[/C][C]1.715[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3292&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
13.3370.2506972096156851.5
22.282416666666670.1915712344763370.671
32.146666666666670.08406418903901880.279
42.257750.1815314272816390.531
53.289750.3819088718053521.715







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.191458248239138
beta0.153757566401261
S.D.0.0578135882715196
T-STAT2.6595402741505
p-value0.0763686390139579

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.191458248239138 \tabularnewline
beta & 0.153757566401261 \tabularnewline
S.D. & 0.0578135882715196 \tabularnewline
T-STAT & 2.6595402741505 \tabularnewline
p-value & 0.0763686390139579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3292&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.191458248239138[/C][/ROW]
[ROW][C]beta[/C][C]0.153757566401261[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0578135882715196[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.6595402741505[/C][/ROW]
[ROW][C]p-value[/C][C]0.0763686390139579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3292&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3292&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-0.191458248239138
beta0.153757566401261
S.D.0.0578135882715196
T-STAT2.6595402741505
p-value0.0763686390139579







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.61731943769505
beta2.06390600022251
S.D.0.849778896924156
T-STAT2.42875647735310
p-value0.0934338471354053
Lambda-1.06390600022251

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.61731943769505 \tabularnewline
beta & 2.06390600022251 \tabularnewline
S.D. & 0.849778896924156 \tabularnewline
T-STAT & 2.42875647735310 \tabularnewline
p-value & 0.0934338471354053 \tabularnewline
Lambda & -1.06390600022251 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3292&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.61731943769505[/C][/ROW]
[ROW][C]beta[/C][C]2.06390600022251[/C][/ROW]
[ROW][C]S.D.[/C][C]0.849778896924156[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.42875647735310[/C][/ROW]
[ROW][C]p-value[/C][C]0.0934338471354053[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.06390600022251[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3292&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3292&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-3.61731943769505
beta2.06390600022251
S.D.0.849778896924156
T-STAT2.42875647735310
p-value0.0934338471354053
Lambda-1.06390600022251



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')