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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 09:19:15 -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/t119626615985w7wiwwovfjj7n.htm/, Retrieved Thu, 02 May 2024 00:04:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7129, Retrieved Thu, 02 May 2024 00:04:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard deviatio...] [2007-11-28 16:19:15] [bebbf4ab6ac77d61a56e6916ab0650f9] [Current]
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Dataseries X:
105,3
101,3
108,4
107,4
109,1
109,5
111,4
110,1
117,0
129,6
113,5
113,3
110,1
107,4
110,1
112,5
106,0
117,6
117,8
113,5
121,2
130,4
115,2
117,9
110,7
107,6
124,3
115,1
112,5
127,9
117,4
119,3
130,4
126,0
125,4
130,5
115,9
108,7
124,0
119,4
118,6
131,3
111,1
124,8
132,3
126,7
131,7
130,9
122,1
113,2
133,6
119,2
129,4
131,4
117,1
130,5
132,3
140,8
137,5
128,6
126,7
120,8
139,3
128,6
131,3
136,3
128,5




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=7129&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=7129&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7129&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
1111.3257.041193726273224.3
2114.9756.7008988542243729.1
3120.5916666666677.9087360596119322.1
4122.958.2031590367259224.9
5127.9758.3891840539416734.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 111.325 & 7.0411937262732 & 24.3 \tabularnewline
2 & 114.975 & 6.70089885422437 & 29.1 \tabularnewline
3 & 120.591666666667 & 7.90873605961193 & 22.1 \tabularnewline
4 & 122.95 & 8.20315903672592 & 24.9 \tabularnewline
5 & 127.975 & 8.38918405394167 & 34.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7129&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]111.325[/C][C]7.0411937262732[/C][C]24.3[/C][/ROW]
[ROW][C]2[/C][C]114.975[/C][C]6.70089885422437[/C][C]29.1[/C][/ROW]
[ROW][C]3[/C][C]120.591666666667[/C][C]7.90873605961193[/C][C]22.1[/C][/ROW]
[ROW][C]4[/C][C]122.95[/C][C]8.20315903672592[/C][C]24.9[/C][/ROW]
[ROW][C]5[/C][C]127.975[/C][C]8.38918405394167[/C][C]34.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7129&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7129&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
1111.3257.041193726273224.3
2114.9756.7008988542243729.1
3120.5916666666677.9087360596119322.1
4122.958.2031590367259224.9
5127.9758.3891840539416734.8







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4.65966796781681
beta0.102943786952289
S.D.0.026609904328626
T-STAT3.86862672187611
p-value0.0305554191721345

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.65966796781681 \tabularnewline
beta & 0.102943786952289 \tabularnewline
S.D. & 0.026609904328626 \tabularnewline
T-STAT & 3.86862672187611 \tabularnewline
p-value & 0.0305554191721345 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7129&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.65966796781681[/C][/ROW]
[ROW][C]beta[/C][C]0.102943786952289[/C][/ROW]
[ROW][C]S.D.[/C][C]0.026609904328626[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.86862672187611[/C][/ROW]
[ROW][C]p-value[/C][C]0.0305554191721345[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7129&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7129&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-4.65966796781681
beta0.102943786952289
S.D.0.026609904328626
T-STAT3.86862672187611
p-value0.0305554191721345







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.71275622980353
beta1.61907419162354
S.D.0.442957045477292
T-STAT3.6551494284936
p-value0.0353647425286487
Lambda-0.619074191623539

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.71275622980353 \tabularnewline
beta & 1.61907419162354 \tabularnewline
S.D. & 0.442957045477292 \tabularnewline
T-STAT & 3.6551494284936 \tabularnewline
p-value & 0.0353647425286487 \tabularnewline
Lambda & -0.619074191623539 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7129&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.71275622980353[/C][/ROW]
[ROW][C]beta[/C][C]1.61907419162354[/C][/ROW]
[ROW][C]S.D.[/C][C]0.442957045477292[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.6551494284936[/C][/ROW]
[ROW][C]p-value[/C][C]0.0353647425286487[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.619074191623539[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7129&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7129&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-5.71275622980353
beta1.61907419162354
S.D.0.442957045477292
T-STAT3.6551494284936
p-value0.0353647425286487
Lambda-0.619074191623539



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')