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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 16 Dec 2010 20:28:35 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/16/t1292531367mpjn8kb9hiezamf.htm/, Retrieved Fri, 03 May 2024 05:58:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111263, Retrieved Fri, 03 May 2024 05:58:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2010-12-16 20:28:35] [e7b77eb06cdf8868fc9cf2043e42b3da] [Current]
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Dataseries X:
4.785
4.109
4.026
4.44
3.828
3.953
4.801
4.104
4.57
4.411
4.839
4.736
3.83
4.248
5.657
3.809
4.578
4.3
5.103
4.121
4.205
5.116
4.219
4.736
4.625
4.146
5.299
5.011
4.731
4.619
5.578
5.369
4.904
6.102
5.04
5.731
5.732
4.491
4.755
5.208
4.962
4.163
5.592
5.761
4.929
5.219
4.429
4.143
4.308
3.996
4.634
4.138
3.759
3.922
5.56
4.004
3.937
5.25
3.908
4.814
4.407
3.243
3.74
3.949
3.711
3.796
4.145
3.499
4.164
3.902
3.186
3.353
3.475
3.032
3.341
3.811
3.655
4.058
3.682
3.348
3.848
3.289
3.851
2.766
2.837
2.734
3.764
3.215
3.287
3.507
3.06
3.734
3.849
4.404
3.497
3.389
2.944
3.098
3.48
3.353
3.958
3.504
3.446
3.794
3.676
4.159
3.914
3.595




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111263&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111263&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111263&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.38350.3669484729743151.011
24.49350.5626640366878071.848
35.096250.5473607959190091.956
44.948666666666670.5730034639484911.618
54.35250.5846611295131881.801
63.757916666666670.3838222738179581.221
73.5130.3764453358843631.292
83.439750.4650323791268341.67
93.576750.3525068987074771.215

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.3835 & 0.366948472974315 & 1.011 \tabularnewline
2 & 4.4935 & 0.562664036687807 & 1.848 \tabularnewline
3 & 5.09625 & 0.547360795919009 & 1.956 \tabularnewline
4 & 4.94866666666667 & 0.573003463948491 & 1.618 \tabularnewline
5 & 4.3525 & 0.584661129513188 & 1.801 \tabularnewline
6 & 3.75791666666667 & 0.383822273817958 & 1.221 \tabularnewline
7 & 3.513 & 0.376445335884363 & 1.292 \tabularnewline
8 & 3.43975 & 0.465032379126834 & 1.67 \tabularnewline
9 & 3.57675 & 0.352506898707477 & 1.215 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111263&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]4.3835[/C][C]0.366948472974315[/C][C]1.011[/C][/ROW]
[ROW][C]2[/C][C]4.4935[/C][C]0.562664036687807[/C][C]1.848[/C][/ROW]
[ROW][C]3[/C][C]5.09625[/C][C]0.547360795919009[/C][C]1.956[/C][/ROW]
[ROW][C]4[/C][C]4.94866666666667[/C][C]0.573003463948491[/C][C]1.618[/C][/ROW]
[ROW][C]5[/C][C]4.3525[/C][C]0.584661129513188[/C][C]1.801[/C][/ROW]
[ROW][C]6[/C][C]3.75791666666667[/C][C]0.383822273817958[/C][C]1.221[/C][/ROW]
[ROW][C]7[/C][C]3.513[/C][C]0.376445335884363[/C][C]1.292[/C][/ROW]
[ROW][C]8[/C][C]3.43975[/C][C]0.465032379126834[/C][C]1.67[/C][/ROW]
[ROW][C]9[/C][C]3.57675[/C][C]0.352506898707477[/C][C]1.215[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111263&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111263&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
14.38350.3669484729743151.011
24.49350.5626640366878071.848
35.096250.5473607959190091.956
44.948666666666670.5730034639484911.618
54.35250.5846611295131881.801
63.757916666666670.3838222738179581.221
73.5130.3764453358843631.292
83.439750.4650323791268341.67
93.576750.3525068987074771.215







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.000501945988153654
beta0.112026674399618
S.D.0.0424762510570128
T-STAT2.63739552365986
p-value0.0335501642315831

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.000501945988153654 \tabularnewline
beta & 0.112026674399618 \tabularnewline
S.D. & 0.0424762510570128 \tabularnewline
T-STAT & 2.63739552365986 \tabularnewline
p-value & 0.0335501642315831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111263&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.000501945988153654[/C][/ROW]
[ROW][C]beta[/C][C]0.112026674399618[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0424762510570128[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.63739552365986[/C][/ROW]
[ROW][C]p-value[/C][C]0.0335501642315831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111263&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111263&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)
alpha0.000501945988153654
beta0.112026674399618
S.D.0.0424762510570128
T-STAT2.63739552365986
p-value0.0335501642315831







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.18803080402238
beta0.992677955437906
S.D.0.393465751027251
T-STAT2.52290816378871
p-value0.0396416650144961
Lambda0.00732204456209395

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.18803080402238 \tabularnewline
beta & 0.992677955437906 \tabularnewline
S.D. & 0.393465751027251 \tabularnewline
T-STAT & 2.52290816378871 \tabularnewline
p-value & 0.0396416650144961 \tabularnewline
Lambda & 0.00732204456209395 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111263&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.18803080402238[/C][/ROW]
[ROW][C]beta[/C][C]0.992677955437906[/C][/ROW]
[ROW][C]S.D.[/C][C]0.393465751027251[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.52290816378871[/C][/ROW]
[ROW][C]p-value[/C][C]0.0396416650144961[/C][/ROW]
[ROW][C]Lambda[/C][C]0.00732204456209395[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111263&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111263&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-2.18803080402238
beta0.992677955437906
S.D.0.393465751027251
T-STAT2.52290816378871
p-value0.0396416650144961
Lambda0.00732204456209395



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')