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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 computationFri, 27 Nov 2009 15:13:36 -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/Nov/27/t12593601324x3lcsbzvbp8a55.htm/, Retrieved Wed, 15 Jan 2025 05:54:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61308, Retrieved Wed, 15 Jan 2025 05:54:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact218

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       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [Workshop 8] [2009-11-24 11:49:44] [214e6e00abbde49700521a7ef1d30da2]
-    D          [(Partial) Autocorrelation Function] [WS 8.2 autocorrel...] [2009-11-27 20:13:42] [d31db4f83c6a129f6d3e47077769e868]
-   P             [(Partial) Autocorrelation Function] [WS 8.4 Autocorrel...] [2009-11-27 20:58:47] [d31db4f83c6a129f6d3e47077769e868]
- RM                [Variance Reduction Matrix] [WS 8.5 Variantie ...] [2009-11-27 21:11:14] [d31db4f83c6a129f6d3e47077769e868]
- RM                  [Spectral Analysis] [WS 8.7 Spectrum a...] [2009-11-27 21:40:54] [d31db4f83c6a129f6d3e47077769e868]
-                       [Spectral Analysis] [WS 8.8 Spectrum a...] [2009-11-27 21:57:05] [d31db4f83c6a129f6d3e47077769e868]
- RM                        [Standard Deviation-Mean Plot] [WS 8.9 Heterosked...] [2009-11-27 22:13:36] [852eae237d08746109043531619a60c9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
474605
470390
461251
454724
455626
516847
525192
522975
518585
509239
512238
519164
517009
509933
509127
500875
506971
569323
579714
577992
565644
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
565724
557274
560576
548854
531673
525919
511038
498662
555362
564591
541667
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516441
528222
532638

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=61308&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=61308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61308&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
1495069.66666666728832.605786231770468
2541753.7530569.737451291778839
3578990.41666666729057.176880508475951
4596609.33333333321826.099586309961428
5585523.66666666723901.235336401868535
6528821.83333333320247.105408532965929
7505831.66666666720459.314910476964233

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 495069.666666667 & 28832.6057862317 & 70468 \tabularnewline
2 & 541753.75 & 30569.7374512917 & 78839 \tabularnewline
3 & 578990.416666667 & 29057.1768805084 & 75951 \tabularnewline
4 & 596609.333333333 & 21826.0995863099 & 61428 \tabularnewline
5 & 585523.666666667 & 23901.2353364018 & 68535 \tabularnewline
6 & 528821.833333333 & 20247.1054085329 & 65929 \tabularnewline
7 & 505831.666666667 & 20459.3149104769 & 64233 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61308&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]495069.666666667[/C][C]28832.6057862317[/C][C]70468[/C][/ROW]
[ROW][C]2[/C][C]541753.75[/C][C]30569.7374512917[/C][C]78839[/C][/ROW]
[ROW][C]3[/C][C]578990.416666667[/C][C]29057.1768805084[/C][C]75951[/C][/ROW]
[ROW][C]4[/C][C]596609.333333333[/C][C]21826.0995863099[/C][C]61428[/C][/ROW]
[ROW][C]5[/C][C]585523.666666667[/C][C]23901.2353364018[/C][C]68535[/C][/ROW]
[ROW][C]6[/C][C]528821.833333333[/C][C]20247.1054085329[/C][C]65929[/C][/ROW]
[ROW][C]7[/C][C]505831.666666667[/C][C]20459.3149104769[/C][C]64233[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61308&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
1495069.66666666728832.605786231770468
2541753.7530569.737451291778839
3578990.41666666729057.176880508475951
4596609.33333333321826.099586309961428
5585523.66666666723901.235336401868535
6528821.83333333320247.105408532965929
7505831.66666666720459.314910476964233






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha26385.3551633024
beta-0.00255810935935412
S.D.0.0489898002903621
T-STAT-0.0522171828460666
p-value0.96037762092614

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 26385.3551633024 \tabularnewline
beta & -0.00255810935935412 \tabularnewline
S.D. & 0.0489898002903621 \tabularnewline
T-STAT & -0.0522171828460666 \tabularnewline
p-value & 0.96037762092614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61308&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]26385.3551633024[/C][/ROW]
[ROW][C]beta[/C][C]-0.00255810935935412[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0489898002903621[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0522171828460666[/C][/ROW]
[ROW][C]p-value[/C][C]0.96037762092614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61308&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)
alpha26385.3551633024
beta-0.00255810935935412
S.D.0.0489898002903621
T-STAT-0.0522171828460666
p-value0.96037762092614






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha10.0277034416390
beta0.00643014869455636
S.D.1.06996519085604
T-STAT0.0060096802676467
p-value0.99543740329015
Lambda0.993569851305444

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 10.0277034416390 \tabularnewline
beta & 0.00643014869455636 \tabularnewline
S.D. & 1.06996519085604 \tabularnewline
T-STAT & 0.0060096802676467 \tabularnewline
p-value & 0.99543740329015 \tabularnewline
Lambda & 0.993569851305444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61308&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.0277034416390[/C][/ROW]
[ROW][C]beta[/C][C]0.00643014869455636[/C][/ROW]
[ROW][C]S.D.[/C][C]1.06996519085604[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0060096802676467[/C][/ROW]
[ROW][C]p-value[/C][C]0.99543740329015[/C][/ROW]
[ROW][C]Lambda[/C][C]0.993569851305444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61308&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61308&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)
alpha10.0277034416390
beta0.00643014869455636
S.D.1.06996519085604
T-STAT0.0060096802676467
p-value0.99543740329015
Lambda0.993569851305444


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 6 ; par6 = MA ; par7 = 0.95 ;
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')