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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 computationTue, 01 Dec 2009 10:08:36 -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/01/t1259687409svuro4o1u54qvmy.htm/, Retrieved Fri, 19 Apr 2024 10:22:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62127, Retrieved Fri, 19 Apr 2024 10:22:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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]
- R  D      [Standard Deviation-Mean Plot] [] [2009-12-01 17:08:36] [6dfcce621b31349cab7f0d189e6f8a9d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
492865
480961
461935
456608
441977
439148
488180
520564
501492
485025
464196
460170
467037
460070
447988
442867
436087
431328
484015
509673
512927
502831
470984
471067
476049
474605
470439
461251
454724
455626
516847
525192
522975
518585
509239
512238
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62127&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]2 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=62127&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62127&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1474426.7524540.069612129981416
2469739.528068.080740487981599
3491480.83333333328234.064982291270468
4538140.530455.563407275078857
5576612.08333333329164.685309021375951
6596397.41666666721872.304573502661428

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 474426.75 & 24540.0696121299 & 81416 \tabularnewline
2 & 469739.5 & 28068.0807404879 & 81599 \tabularnewline
3 & 491480.833333333 & 28234.0649822912 & 70468 \tabularnewline
4 & 538140.5 & 30455.5634072750 & 78857 \tabularnewline
5 & 576612.083333333 & 29164.6853090213 & 75951 \tabularnewline
6 & 596397.416666667 & 21872.3045735026 & 61428 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62127&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]474426.75[/C][C]24540.0696121299[/C][C]81416[/C][/ROW]
[ROW][C]2[/C][C]469739.5[/C][C]28068.0807404879[/C][C]81599[/C][/ROW]
[ROW][C]3[/C][C]491480.833333333[/C][C]28234.0649822912[/C][C]70468[/C][/ROW]
[ROW][C]4[/C][C]538140.5[/C][C]30455.5634072750[/C][C]78857[/C][/ROW]
[ROW][C]5[/C][C]576612.083333333[/C][C]29164.6853090213[/C][C]75951[/C][/ROW]
[ROW][C]6[/C][C]596397.416666667[/C][C]21872.3045735026[/C][C]61428[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62127&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62127&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
1474426.7524540.069612129981416
2469739.528068.080740487981599
3491480.83333333328234.064982291270468
4538140.530455.563407275078857
5576612.08333333329164.685309021375951
6596397.41666666721872.304573502661428






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha33662.8869458416
beta-0.0125977468519671
S.D.0.0289846810055491
T-STAT-0.434634655787838
p-value0.686247491527298

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 33662.8869458416 \tabularnewline
beta & -0.0125977468519671 \tabularnewline
S.D. & 0.0289846810055491 \tabularnewline
T-STAT & -0.434634655787838 \tabularnewline
p-value & 0.686247491527298 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62127&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]33662.8869458416[/C][/ROW]
[ROW][C]beta[/C][C]-0.0125977468519671[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0289846810055491[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.434634655787838[/C][/ROW]
[ROW][C]p-value[/C][C]0.686247491527298[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62127&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62127&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)
alpha33662.8869458416
beta-0.0125977468519671
S.D.0.0289846810055491
T-STAT-0.434634655787838
p-value0.686247491527298






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha13.8050220190586
beta-0.273863367334125
S.D.0.591372456245996
T-STAT-0.463097941815885
p-value0.667368504380674
Lambda1.27386336733413

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 13.8050220190586 \tabularnewline
beta & -0.273863367334125 \tabularnewline
S.D. & 0.591372456245996 \tabularnewline
T-STAT & -0.463097941815885 \tabularnewline
p-value & 0.667368504380674 \tabularnewline
Lambda & 1.27386336733413 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62127&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.8050220190586[/C][/ROW]
[ROW][C]beta[/C][C]-0.273863367334125[/C][/ROW]
[ROW][C]S.D.[/C][C]0.591372456245996[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.463097941815885[/C][/ROW]
[ROW][C]p-value[/C][C]0.667368504380674[/C][/ROW]
[ROW][C]Lambda[/C][C]1.27386336733413[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62127&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62127&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)
alpha13.8050220190586
beta-0.273863367334125
S.D.0.591372456245996
T-STAT-0.463097941815885
p-value0.667368504380674
Lambda1.27386336733413


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')