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Description of Statistical Computation

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 computationSun, 18 Dec 2016 16:26:40 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/18/t14820748081c3laywfb4e1xpf.htm/, Retrieved Wed, 08 May 2024 23:20:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301135, Retrieved Wed, 08 May 2024 23:20:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2016-12-18 15:26:40] [94ac3c9a028ddd47e8862e80eac9f626] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3830.8
3732.6
3733.5
3808.5
3860.5
3844.4
3864.5
3803.1
3756.1
3771.1
3754.4
3759.6
3783.5
3886.5
3944.4
4012.1
4089.5
4144
4166.4
4194.2
4221.8
4254.8
4309
4333.5
4390.5
4387.7
4412.6
4427.1
4460
4515.3
4559.3
4625.5
4655.3
4704.8
4734.5
4779.7
4817.6
4839
4839
4856.7
4890.8
4902.7
4882.6
4833.8
4796.7

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301135&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301135&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301135&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13793.2583333333348.3509040685118131.9
24111.64166666667172.783708503558550
34554.35833333333142.21656634311392

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3793.25833333333 & 48.3509040685118 & 131.9 \tabularnewline
2 & 4111.64166666667 & 172.783708503558 & 550 \tabularnewline
3 & 4554.35833333333 & 142.21656634311 & 392 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301135&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]3793.25833333333[/C][C]48.3509040685118[/C][C]131.9[/C][/ROW]
[ROW][C]2[/C][C]4111.64166666667[/C][C]172.783708503558[/C][C]550[/C][/ROW]
[ROW][C]3[/C][C]4554.35833333333[/C][C]142.21656634311[/C][C]392[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301135&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301135&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13793.2583333333348.3509040685118131.9
24111.64166666667172.783708503558550
34554.35833333333142.21656634311392






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-340.912784298788
beta0.111249762604506
S.D.0.128071476660188
T-STAT0.868653704209915
p-value0.544674060758658

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -340.912784298788 \tabularnewline
beta & 0.111249762604506 \tabularnewline
S.D. & 0.128071476660188 \tabularnewline
T-STAT & 0.868653704209915 \tabularnewline
p-value & 0.544674060758658 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301135&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-340.912784298788[/C][/ROW]
[ROW][C]beta[/C][C]0.111249762604506[/C][/ROW]
[ROW][C]S.D.[/C][C]0.128071476660188[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.868653704209915[/C][/ROW]
[ROW][C]p-value[/C][C]0.544674060758658[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301135&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301135&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-340.912784298788
beta0.111249762604506
S.D.0.128071476660188
T-STAT0.868653704209915
p-value0.544674060758658






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-41.6194318129602
beta5.55687020712619
S.D.5.01587639987764
T-STAT1.10785628753965
p-value0.46745337247634
Lambda-4.55687020712619

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -41.6194318129602 \tabularnewline
beta & 5.55687020712619 \tabularnewline
S.D. & 5.01587639987764 \tabularnewline
T-STAT & 1.10785628753965 \tabularnewline
p-value & 0.46745337247634 \tabularnewline
Lambda & -4.55687020712619 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301135&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-41.6194318129602[/C][/ROW]
[ROW][C]beta[/C][C]5.55687020712619[/C][/ROW]
[ROW][C]S.D.[/C][C]5.01587639987764[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.10785628753965[/C][/ROW]
[ROW][C]p-value[/C][C]0.46745337247634[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.55687020712619[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301135&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301135&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-41.6194318129602
beta5.55687020712619
S.D.5.01587639987764
T-STAT1.10785628753965
p-value0.46745337247634
Lambda-4.55687020712619


Figures (Output of Computation)

Input Parameters & R Code

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