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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 computationWed, 25 Nov 2009 13:48:16 -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/2009/Nov/25/t12591823820h6czffnfs4ocr6.htm/, Retrieved Tue, 07 May 2024 15:04:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59641, Retrieved Tue, 07 May 2024 15:04:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
- R PD          [Standard Deviation-Mean Plot] [SMP] [2009-11-25 20:48:16] [026d431dc78a3ce53a040b5408fc0322] [Current]
- RMPD            [(Partial) Autocorrelation Function] [smp] [2009-12-02 19:34:54] [1f74ef2f756548f1f3a7b6136ea56d7f]
- RMPD            [(Partial) Autocorrelation Function] [SMP] [2009-12-02 19:34:54] [1f74ef2f756548f1f3a7b6136ea56d7f]
-   PD            [Standard Deviation-Mean Plot] [SMP] [2009-12-02 19:43:22] [1f74ef2f756548f1f3a7b6136ea56d7f]
-   PD              [Standard Deviation-Mean Plot] [workshop 8 SMP] [2009-12-04 13:49:53] [af8eb90b4bf1bcfcc4325c143dbee260]
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Dataseries X:
5250,0
3937,0
4004,0
5560,0
3922,0
3759,0
4138,0
4634,0
3996,0
4308,0
4143,0
4429,0
5219,0
4929,0
5755,0
5592,0
4163,0
4962,0
5208,0
4755,0
4491,0
5732,0
5731,0
5040,0
6102,0
4904,0
5369,0
5578,0
4619,0
4731,0
5011,0
5299,0
4146,0
4625,0
4736,0
4219,0
5116,0
4205,0
4121,0
5103,0
4300,0
4578,0
3809,0
5526,0
4247,0
3830,0
4394,0
4826,0
4409,0
4569,0
4106,0
4794,0
3914,0
3793,0
4405,0
4022,0
4100,0
4788,0
3163,0
3585,0
3903,0




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=59641&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=59641&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59641&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
14340555.748471555581801
25131.41666666667513.6690583587371592
34944.91666666667565.2108952069181956
44504.58333333333537.6836613632311717
54137.33333333333488.4931065547551631

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4340 & 555.74847155558 & 1801 \tabularnewline
2 & 5131.41666666667 & 513.669058358737 & 1592 \tabularnewline
3 & 4944.91666666667 & 565.210895206918 & 1956 \tabularnewline
4 & 4504.58333333333 & 537.683661363231 & 1717 \tabularnewline
5 & 4137.33333333333 & 488.493106554755 & 1631 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59641&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]4340[/C][C]555.74847155558[/C][C]1801[/C][/ROW]
[ROW][C]2[/C][C]5131.41666666667[/C][C]513.669058358737[/C][C]1592[/C][/ROW]
[ROW][C]3[/C][C]4944.91666666667[/C][C]565.210895206918[/C][C]1956[/C][/ROW]
[ROW][C]4[/C][C]4504.58333333333[/C][C]537.683661363231[/C][C]1717[/C][/ROW]
[ROW][C]5[/C][C]4137.33333333333[/C][C]488.493106554755[/C][C]1631[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59641&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59641&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
14340555.748471555581801
25131.41666666667513.6690583587371592
34944.91666666667565.2108952069181956
44504.58333333333537.6836613632311717
54137.33333333333488.4931065547551631







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha431.34199357168
beta0.0218618162775069
S.D.0.0416445983041017
T-STAT0.524961631707074
p-value0.635934085091851

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 431.34199357168 \tabularnewline
beta & 0.0218618162775069 \tabularnewline
S.D. & 0.0416445983041017 \tabularnewline
T-STAT & 0.524961631707074 \tabularnewline
p-value & 0.635934085091851 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59641&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]431.34199357168[/C][/ROW]
[ROW][C]beta[/C][C]0.0218618162775069[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0416445983041017[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.524961631707074[/C][/ROW]
[ROW][C]p-value[/C][C]0.635934085091851[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59641&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59641&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)
alpha431.34199357168
beta0.0218618162775069
S.D.0.0416445983041017
T-STAT0.524961631707074
p-value0.635934085091851







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.4911544513223
beta0.211592630905648
S.D.0.363029512181478
T-STAT0.582852423303461
p-value0.600911379587641
Lambda0.788407369094352

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.4911544513223 \tabularnewline
beta & 0.211592630905648 \tabularnewline
S.D. & 0.363029512181478 \tabularnewline
T-STAT & 0.582852423303461 \tabularnewline
p-value & 0.600911379587641 \tabularnewline
Lambda & 0.788407369094352 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59641&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.4911544513223[/C][/ROW]
[ROW][C]beta[/C][C]0.211592630905648[/C][/ROW]
[ROW][C]S.D.[/C][C]0.363029512181478[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.582852423303461[/C][/ROW]
[ROW][C]p-value[/C][C]0.600911379587641[/C][/ROW]
[ROW][C]Lambda[/C][C]0.788407369094352[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59641&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59641&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)
alpha4.4911544513223
beta0.211592630905648
S.D.0.363029512181478
T-STAT0.582852423303461
p-value0.600911379587641
Lambda0.788407369094352



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 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')