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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, 02 Dec 2009 08:40:33 -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/02/t1259768560vwbbzj43iw9xepz.htm/, Retrieved Sun, 28 Apr 2024 05:28:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62379, Retrieved Sun, 28 Apr 2024 05:28:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D      [Standard Deviation-Mean Plot] [] [2009-12-02 15:40:33] [830aa0f7fb5acd5849dbc0c6ad889830] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519164
517009
509933
509127
500857
506971
569323
579714
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141

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=62379&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=62379&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62379&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
1538140.530455.563407275078857
2576612.08333333329164.685309021375951
3596397.41666666721872.304573502661428
4588261.16666666722629.620286989668535
5532458.83333333321778.072975246365929
650486519560.160730888264233

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 538140.5 & 30455.5634072750 & 78857 \tabularnewline
2 & 576612.083333333 & 29164.6853090213 & 75951 \tabularnewline
3 & 596397.416666667 & 21872.3045735026 & 61428 \tabularnewline
4 & 588261.166666667 & 22629.6202869896 & 68535 \tabularnewline
5 & 532458.833333333 & 21778.0729752463 & 65929 \tabularnewline
6 & 504865 & 19560.1607308882 & 64233 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62379&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]538140.5[/C][C]30455.5634072750[/C][C]78857[/C][/ROW]
[ROW][C]2[/C][C]576612.083333333[/C][C]29164.6853090213[/C][C]75951[/C][/ROW]
[ROW][C]3[/C][C]596397.416666667[/C][C]21872.3045735026[/C][C]61428[/C][/ROW]
[ROW][C]4[/C][C]588261.166666667[/C][C]22629.6202869896[/C][C]68535[/C][/ROW]
[ROW][C]5[/C][C]532458.833333333[/C][C]21778.0729752463[/C][C]65929[/C][/ROW]
[ROW][C]6[/C][C]504865[/C][C]19560.1607308882[/C][C]64233[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62379&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62379&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
1538140.530455.563407275078857
2576612.08333333329164.685309021375951
3596397.41666666721872.304573502661428
4588261.16666666722629.620286989668535
5532458.83333333321778.072975246365929
650486519560.160730888264233






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha12407.4892423576
beta0.0212829223263990
S.D.0.0603890238344307
T-STAT0.352430308937444
p-value0.742301186535253

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 12407.4892423576 \tabularnewline
beta & 0.0212829223263990 \tabularnewline
S.D. & 0.0603890238344307 \tabularnewline
T-STAT & 0.352430308937444 \tabularnewline
p-value & 0.742301186535253 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62379&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12407.4892423576[/C][/ROW]
[ROW][C]beta[/C][C]0.0212829223263990[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0603890238344307[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.352430308937444[/C][/ROW]
[ROW][C]p-value[/C][C]0.742301186535253[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62379&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62379&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)
alpha12407.4892423576
beta0.0212829223263990
S.D.0.0603890238344307
T-STAT0.352430308937444
p-value0.742301186535253






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.90031508505513
beta0.618594993440069
S.D.1.31474167144922
T-STAT0.470506873611302
p-value0.662501920268405
Lambda0.381405006559931

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.90031508505513 \tabularnewline
beta & 0.618594993440069 \tabularnewline
S.D. & 1.31474167144922 \tabularnewline
T-STAT & 0.470506873611302 \tabularnewline
p-value & 0.662501920268405 \tabularnewline
Lambda & 0.381405006559931 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62379&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.90031508505513[/C][/ROW]
[ROW][C]beta[/C][C]0.618594993440069[/C][/ROW]
[ROW][C]S.D.[/C][C]1.31474167144922[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.470506873611302[/C][/ROW]
[ROW][C]p-value[/C][C]0.662501920268405[/C][/ROW]
[ROW][C]Lambda[/C][C]0.381405006559931[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62379&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62379&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)
alpha1.90031508505513
beta0.618594993440069
S.D.1.31474167144922
T-STAT0.470506873611302
p-value0.662501920268405
Lambda0.381405006559931


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')