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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 02 Jun 2009 12:38:18 -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/2009/Jun/02/t1243967924bn7paxb8w5tyy06.htm/, Retrieved Thu, 09 May 2024 22:55:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41365, Retrieved Thu, 09 May 2024 22:55:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

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] [opgave8oef3-Merel...] [2009-06-02 18:38:18] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
672.1
674.4
676.6
678.7
680.8
682.9
684
684.1
684.1
684.2
685.9
689.2
692.4
695.7
697.2
696.8
696.4
695.9
696.2
697.2
705.2
706.2
707.4
708.7
710
711.3
711.5
710.7
710
709.2
707.9
706.1
704.4
702.7
701.5
700.8
700
699.3
698.8
698.4
696.8
695.1
694.3
693.4
692.4
691
689.7
688.3
686
683.6
682.6
681.9
681
679.9
678.5
677.5
678
679
679.8
681.3
684.2
687
688.4
689.5
691.1
693.3
695.9
698
699.6
701.6
703.5
705.5
708.1
709.6
710.3

Tables (Output of Computation)





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=41365&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=41365&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41365&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 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
1681.4166666666675.033493876628917.1000000000000
2699.6083333333335.5634290167344216.3000000000001
3707.1753.9365709582187110.7000000000000
4694.7916666666673.9428781212190411.7000000000000
5680.7583333333332.498529870774328.5
6694.86.9354163537598821.3000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 681.416666666667 & 5.0334938766289 & 17.1000000000000 \tabularnewline
2 & 699.608333333333 & 5.56342901673442 & 16.3000000000001 \tabularnewline
3 & 707.175 & 3.93657095821871 & 10.7000000000000 \tabularnewline
4 & 694.791666666667 & 3.94287812121904 & 11.7000000000000 \tabularnewline
5 & 680.758333333333 & 2.49852987077432 & 8.5 \tabularnewline
6 & 694.8 & 6.93541635375988 & 21.3000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41365&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]681.416666666667[/C][C]5.0334938766289[/C][C]17.1000000000000[/C][/ROW]
[ROW][C]2[/C][C]699.608333333333[/C][C]5.56342901673442[/C][C]16.3000000000001[/C][/ROW]
[ROW][C]3[/C][C]707.175[/C][C]3.93657095821871[/C][C]10.7000000000000[/C][/ROW]
[ROW][C]4[/C][C]694.791666666667[/C][C]3.94287812121904[/C][C]11.7000000000000[/C][/ROW]
[ROW][C]5[/C][C]680.758333333333[/C][C]2.49852987077432[/C][C]8.5[/C][/ROW]
[ROW][C]6[/C][C]694.8[/C][C]6.93541635375988[/C][C]21.3000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41365&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41365&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
1681.4166666666675.033493876628917.1000000000000
2699.6083333333335.5634290167344216.3000000000001
3707.1753.9365709582187110.7000000000000
4694.7916666666673.9428781212190411.7000000000000
5680.7583333333332.498529870774328.5
6694.86.9354163537598821.3000000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-22.117756039696
beta0.0386232832202357
S.D.0.071836878895163
T-STAT0.53765257920798
p-value0.61933457174021

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -22.117756039696 \tabularnewline
beta & 0.0386232832202357 \tabularnewline
S.D. & 0.071836878895163 \tabularnewline
T-STAT & 0.53765257920798 \tabularnewline
p-value & 0.61933457174021 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41365&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-22.117756039696[/C][/ROW]
[ROW][C]beta[/C][C]0.0386232832202357[/C][/ROW]
[ROW][C]S.D.[/C][C]0.071836878895163[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.53765257920798[/C][/ROW]
[ROW][C]p-value[/C][C]0.61933457174021[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41365&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41365&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-22.117756039696
beta0.0386232832202357
S.D.0.071836878895163
T-STAT0.53765257920798
p-value0.61933457174021






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-49.4658015719107
beta7.78979923244573
S.D.11.1737584513255
T-STAT0.697151210703115
p-value0.524102442250078
Lambda-6.78979923244573

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -49.4658015719107 \tabularnewline
beta & 7.78979923244573 \tabularnewline
S.D. & 11.1737584513255 \tabularnewline
T-STAT & 0.697151210703115 \tabularnewline
p-value & 0.524102442250078 \tabularnewline
Lambda & -6.78979923244573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41365&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-49.4658015719107[/C][/ROW]
[ROW][C]beta[/C][C]7.78979923244573[/C][/ROW]
[ROW][C]S.D.[/C][C]11.1737584513255[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.697151210703115[/C][/ROW]
[ROW][C]p-value[/C][C]0.524102442250078[/C][/ROW]
[ROW][C]Lambda[/C][C]-6.78979923244573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41365&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41365&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-49.4658015719107
beta7.78979923244573
S.D.11.1737584513255
T-STAT0.697151210703115
p-value0.524102442250078
Lambda-6.78979923244573


Figures (Output of Computation)

Input Parameters & R Code

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')