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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 19 May 2008 09:05:08 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/19/t1211209555icwpnwbd7ed6t9z.htm/, Retrieved Tue, 14 May 2024 18:25:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12885, Retrieved Tue, 14 May 2024 18:25:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Mean Plot Eigen R...] [2008-05-19 15:05:08] [88615a9036e6e98ff64037322024b7ad] [Current]
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Dataseries X:
8.16
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.43
8.68
8.68
8.68
8.68
8.68
8.68
8.68
8.68
8.68
8.68
8.68
8.68
8.92
8.92
8.92
8.92
8.92
8.92
8.92
8.92
8.92
8.92
8.92
8.92
9.3
9.3
9.3
9.3
9.3
9.3
9.3
9.3
9.3
9.3
9.3
9.3
9.6
9.6
9.6
9.6
9.6
9.6
9.6
9.6
9.6
9.6
9.6
9.6
9.9
9.9
9.9
9.9
9.9
9.9
9.9
9.9
9.9
9.9
9.9
9.9
10.2
10.2
10.2
10.2
10.2
10.2
10.2
10.2
10.2
10.2
10.2




Summary of computational 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 computational 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=12885&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]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=12885&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12885&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
18.40750.07794228634059940.270000000000000
28.638333333333330.09731236802019040.25
38.880.09341987329938280.24
49.236666666666670.1479147993906900.380000000000001
59.550.1167748416242280.299999999999999
69.850.1167748416242290.300000000000001
710.150.1167748416242280.299999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.4075 & 0.0779422863405994 & 0.270000000000000 \tabularnewline
2 & 8.63833333333333 & 0.0973123680201904 & 0.25 \tabularnewline
3 & 8.88 & 0.0934198732993828 & 0.24 \tabularnewline
4 & 9.23666666666667 & 0.147914799390690 & 0.380000000000001 \tabularnewline
5 & 9.55 & 0.116774841624228 & 0.299999999999999 \tabularnewline
6 & 9.85 & 0.116774841624229 & 0.300000000000001 \tabularnewline
7 & 10.15 & 0.116774841624228 & 0.299999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12885&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]8.4075[/C][C]0.0779422863405994[/C][C]0.270000000000000[/C][/ROW]
[ROW][C]2[/C][C]8.63833333333333[/C][C]0.0973123680201904[/C][C]0.25[/C][/ROW]
[ROW][C]3[/C][C]8.88[/C][C]0.0934198732993828[/C][C]0.24[/C][/ROW]
[ROW][C]4[/C][C]9.23666666666667[/C][C]0.147914799390690[/C][C]0.380000000000001[/C][/ROW]
[ROW][C]5[/C][C]9.55[/C][C]0.116774841624228[/C][C]0.299999999999999[/C][/ROW]
[ROW][C]6[/C][C]9.85[/C][C]0.116774841624229[/C][C]0.300000000000001[/C][/ROW]
[ROW][C]7[/C][C]10.15[/C][C]0.116774841624228[/C][C]0.299999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12885&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12885&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
18.40750.07794228634059940.270000000000000
28.638333333333330.09731236802019040.25
38.880.09341987329938280.24
49.236666666666670.1479147993906900.380000000000001
59.550.1167748416242280.299999999999999
69.850.1167748416242290.300000000000001
710.150.1167748416242280.299999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0863645367641452
beta0.0211932101104510
S.D.0.0124516485561579
T-STAT1.70204049808088
p-value0.149483049785013

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0863645367641452 \tabularnewline
beta & 0.0211932101104510 \tabularnewline
S.D. & 0.0124516485561579 \tabularnewline
T-STAT & 1.70204049808088 \tabularnewline
p-value & 0.149483049785013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12885&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0863645367641452[/C][/ROW]
[ROW][C]beta[/C][C]0.0211932101104510[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0124516485561579[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.70204049808088[/C][/ROW]
[ROW][C]p-value[/C][C]0.149483049785013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12885&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12885&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-0.0863645367641452
beta0.0211932101104510
S.D.0.0124516485561579
T-STAT1.70204049808088
p-value0.149483049785013







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.69712328608441
beta2.01069505105049
S.D.0.975790765976838
T-STAT2.06058011733451
p-value0.094363532591579
Lambda-1.01069505105049

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.69712328608441 \tabularnewline
beta & 2.01069505105049 \tabularnewline
S.D. & 0.975790765976838 \tabularnewline
T-STAT & 2.06058011733451 \tabularnewline
p-value & 0.094363532591579 \tabularnewline
Lambda & -1.01069505105049 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12885&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.69712328608441[/C][/ROW]
[ROW][C]beta[/C][C]2.01069505105049[/C][/ROW]
[ROW][C]S.D.[/C][C]0.975790765976838[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.06058011733451[/C][/ROW]
[ROW][C]p-value[/C][C]0.094363532591579[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.01069505105049[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12885&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12885&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-6.69712328608441
beta2.01069505105049
S.D.0.975790765976838
T-STAT2.06058011733451
p-value0.094363532591579
Lambda-1.01069505105049



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')