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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, 14 May 2008 00:23:07 -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/14/t1210746946cvp8iotihub3sfe.htm/, Retrieved Tue, 14 May 2024 00:15:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12513, Retrieved Tue, 14 May 2024 00:15:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact243
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation Plot] [Van Passen Glenn ...] [2008-05-12 19:51:47] [447a393a477391846fb1ef840a8b4411]
- RM D    [Standard Deviation-Mean Plot] [Glenn Van Passen ...] [2008-05-14 06:23:07] [7568f24034461b5d7b2d183bbb217711] [Current]
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Dataseries X:
11835.70
11542.20
13093.70
11180.20
12035.70
12112.00
10875.20
9897.30
11672.10
12385.70
11405.60
9830.90
11025.10
10853.80
12252.60
11839.40
11669.10
11601.40
11178.40
9516.40
12102.80
12989.00
11610.20
10205.50
11356.20
11307.10
12648.60
11947.20
11714.10
12192.50
11268.80
9097.40
12639.80
13040.10
11687.30
11191.70
11391.90
11793.10
13933.20
12778.10
11810.30
13698.40
11956.60
10723.80
13938.90
13979.80
13807.40
12973.90
12509.80
12934.10
14908.30
13772.10
13012.60
14049.90
11816.50
11593.20
14466.20
13615.90
14733.90
13880.70
13527.50
13584.00
16170.20
13260.60
14741.90
15486.50
13154.50
12621.20
15031.60
15452.40
15428.00
13105.90
14716.80
14180.00
16202.20
14392.40
15140.60
15960.10
14729.90
13705.20
15728.50
17315.60
16152.80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12513&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]3 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=12513&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12513&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
111488.8583333333952.7265805030163262.8
211403.6416666667932.1831584154123472.6
311674.23333333331016.472916361753942.7
412732.11666666671158.705907336703256
513441.11084.639858117983315.1
614297.0251205.382893618153549

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 11488.8583333333 & 952.726580503016 & 3262.8 \tabularnewline
2 & 11403.6416666667 & 932.183158415412 & 3472.6 \tabularnewline
3 & 11674.2333333333 & 1016.47291636175 & 3942.7 \tabularnewline
4 & 12732.1166666667 & 1158.70590733670 & 3256 \tabularnewline
5 & 13441.1 & 1084.63985811798 & 3315.1 \tabularnewline
6 & 14297.025 & 1205.38289361815 & 3549 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12513&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]11488.8583333333[/C][C]952.726580503016[/C][C]3262.8[/C][/ROW]
[ROW][C]2[/C][C]11403.6416666667[/C][C]932.183158415412[/C][C]3472.6[/C][/ROW]
[ROW][C]3[/C][C]11674.2333333333[/C][C]1016.47291636175[/C][C]3942.7[/C][/ROW]
[ROW][C]4[/C][C]12732.1166666667[/C][C]1158.70590733670[/C][C]3256[/C][/ROW]
[ROW][C]5[/C][C]13441.1[/C][C]1084.63985811798[/C][C]3315.1[/C][/ROW]
[ROW][C]6[/C][C]14297.025[/C][C]1205.38289361815[/C][C]3549[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12513&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12513&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
111488.8583333333952.7265805030163262.8
211403.6416666667932.1831584154123472.6
311674.23333333331016.472916361753942.7
412732.11666666671158.705907336703256
513441.11084.639858117983315.1
614297.0251205.382893618153549







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha11.9542000242275
beta0.0836705652674251
S.D.0.0203151087066643
T-STAT4.11863733911389
p-value0.0146286834830385

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 11.9542000242275 \tabularnewline
beta & 0.0836705652674251 \tabularnewline
S.D. & 0.0203151087066643 \tabularnewline
T-STAT & 4.11863733911389 \tabularnewline
p-value & 0.0146286834830385 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12513&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.9542000242275[/C][/ROW]
[ROW][C]beta[/C][C]0.0836705652674251[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0203151087066643[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.11863733911389[/C][/ROW]
[ROW][C]p-value[/C][C]0.0146286834830385[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12513&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12513&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)
alpha11.9542000242275
beta0.0836705652674251
S.D.0.0203151087066643
T-STAT4.11863733911389
p-value0.0146286834830385







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.53774636851406
beta1.00714580165401
S.D.0.238609473326127
T-STAT4.22089612627182
p-value0.0134679112302602
Lambda-0.00714580165401135

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.53774636851406 \tabularnewline
beta & 1.00714580165401 \tabularnewline
S.D. & 0.238609473326127 \tabularnewline
T-STAT & 4.22089612627182 \tabularnewline
p-value & 0.0134679112302602 \tabularnewline
Lambda & -0.00714580165401135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12513&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.53774636851406[/C][/ROW]
[ROW][C]beta[/C][C]1.00714580165401[/C][/ROW]
[ROW][C]S.D.[/C][C]0.238609473326127[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.22089612627182[/C][/ROW]
[ROW][C]p-value[/C][C]0.0134679112302602[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.00714580165401135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12513&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12513&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-2.53774636851406
beta1.00714580165401
S.D.0.238609473326127
T-STAT4.22089612627182
p-value0.0134679112302602
Lambda-0.00714580165401135



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')