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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 computationWed, 09 Dec 2009 15:25:58 -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/Dec/09/t1260397861duknmqfn0m29pz4.htm/, Retrieved Mon, 29 Apr 2024 14:07:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65221, Retrieved Mon, 29 Apr 2024 14:07:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

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]
-    D        [Standard Deviation-Mean Plot] [WS8 berekening9 TVD] [2009-11-25 15:59:01] [42ad1186d39724f834063794eac7cea3]
-               [Standard Deviation-Mean Plot] [BDM9] [2009-11-25 17:18:31] [f5d341d4bbba73282fc6e80153a6d315]
-    D              [Standard Deviation-Mean Plot] [paper] [2009-12-09 22:25:58] [d447d4b3e35da686436a520338c962fc] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
595
591
612
595
597
589
584
573
567
569
621
629
628
593
588
566
557
590
580
574
573
573
620
626
620
561
527
510
514
549
532
526
511
499
555
565
542
517
506
502
516
508
493
490
469
478
528
534
518
528
533
536
537
524
536
587
597
581
564
558

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=65221&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=65221&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65221&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
1593.519.575030477161962
258923.817487845545971
3539.08333333333333.4241565701252121
4506.91666666666722.100836402656173
5549.91666666666726.684889606916779

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 593.5 & 19.5750304771619 & 62 \tabularnewline
2 & 589 & 23.8174878455459 & 71 \tabularnewline
3 & 539.083333333333 & 33.4241565701252 & 121 \tabularnewline
4 & 506.916666666667 & 22.1008364026561 & 73 \tabularnewline
5 & 549.916666666667 & 26.6848896069167 & 79 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65221&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]593.5[/C][C]19.5750304771619[/C][C]62[/C][/ROW]
[ROW][C]2[/C][C]589[/C][C]23.8174878455459[/C][C]71[/C][/ROW]
[ROW][C]3[/C][C]539.083333333333[/C][C]33.4241565701252[/C][C]121[/C][/ROW]
[ROW][C]4[/C][C]506.916666666667[/C][C]22.1008364026561[/C][C]73[/C][/ROW]
[ROW][C]5[/C][C]549.916666666667[/C][C]26.6848896069167[/C][C]79[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65221&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65221&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
1593.519.575030477161962
258923.817487845545971
3539.08333333333333.4241565701252121
4506.91666666666722.100836402656173
5549.91666666666726.684889606916779






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha51.9873291390615
beta-0.0483492078076489
S.D.0.0801540876731358
T-STAT-0.603203270241368
p-value0.588926172175296

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 51.9873291390615 \tabularnewline
beta & -0.0483492078076489 \tabularnewline
S.D. & 0.0801540876731358 \tabularnewline
T-STAT & -0.603203270241368 \tabularnewline
p-value & 0.588926172175296 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65221&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]51.9873291390615[/C][/ROW]
[ROW][C]beta[/C][C]-0.0483492078076489[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0801540876731358[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.603203270241368[/C][/ROW]
[ROW][C]p-value[/C][C]0.588926172175296[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65221&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65221&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)
alpha51.9873291390615
beta-0.0483492078076489
S.D.0.0801540876731358
T-STAT-0.603203270241368
p-value0.588926172175296






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha9.53290872632687
beta-1.00121642943304
S.D.1.69484070447074
T-STAT-0.590743676849381
p-value0.596243509862978
Lambda2.00121642943304

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.53290872632687 \tabularnewline
beta & -1.00121642943304 \tabularnewline
S.D. & 1.69484070447074 \tabularnewline
T-STAT & -0.590743676849381 \tabularnewline
p-value & 0.596243509862978 \tabularnewline
Lambda & 2.00121642943304 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65221&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.53290872632687[/C][/ROW]
[ROW][C]beta[/C][C]-1.00121642943304[/C][/ROW]
[ROW][C]S.D.[/C][C]1.69484070447074[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.590743676849381[/C][/ROW]
[ROW][C]p-value[/C][C]0.596243509862978[/C][/ROW]
[ROW][C]Lambda[/C][C]2.00121642943304[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65221&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65221&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)
alpha9.53290872632687
beta-1.00121642943304
S.D.1.69484070447074
T-STAT-0.590743676849381
p-value0.596243509862978
Lambda2.00121642943304


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')