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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 computationSat, 13 Dec 2008 11:45:31 -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/2008/Dec/13/t1229194040wwehv6m5qqytoh9.htm/, Retrieved Sun, 19 May 2024 07:44:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33203, Retrieved Sun, 19 May 2024 07:44:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Variance Reduction Matrix] [Unemployment - St...] [2008-12-08 17:18:29] [57850c80fd59ccfb28f882be994e814e]
F       [Variance Reduction Matrix] [STEP 1 1] [2008-12-08 18:47:26] [547636b63517c1c2916a747d66b36ebf]
- RM        [Standard Deviation-Mean Plot] [SD mean plot step 1] [2008-12-13 18:45:31] [35348cd8592af0baf5f138bd59921307] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33203&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33203&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1558009.91666666713846.729442910043052
2591008.91666666715697.036879953045157
3597142.83333333320950.694363990356109
4562721.2543097.969939799127147
5513922.41666666729563.607097727295234

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 558009.916666667 & 13846.7294429100 & 43052 \tabularnewline
2 & 591008.916666667 & 15697.0368799530 & 45157 \tabularnewline
3 & 597142.833333333 & 20950.6943639903 & 56109 \tabularnewline
4 & 562721.25 & 43097.969939799 & 127147 \tabularnewline
5 & 513922.416666667 & 29563.6070977272 & 95234 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33203&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]558009.916666667[/C][C]13846.7294429100[/C][C]43052[/C][/ROW]
[ROW][C]2[/C][C]591008.916666667[/C][C]15697.0368799530[/C][C]45157[/C][/ROW]
[ROW][C]3[/C][C]597142.833333333[/C][C]20950.6943639903[/C][C]56109[/C][/ROW]
[ROW][C]4[/C][C]562721.25[/C][C]43097.969939799[/C][C]127147[/C][/ROW]
[ROW][C]5[/C][C]513922.416666667[/C][C]29563.6070977272[/C][C]95234[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33203&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
1558009.91666666713846.729442910043052
2591008.91666666715697.036879953045157
3597142.83333333320950.694363990356109
4562721.2543097.969939799127147
5513922.41666666729563.607097727295234






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha98151.9153207162
beta-0.130226315834933
S.D.0.195427306801162
T-STAT-0.666367039317757
p-value0.552841417243748

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 98151.9153207162 \tabularnewline
beta & -0.130226315834933 \tabularnewline
S.D. & 0.195427306801162 \tabularnewline
T-STAT & -0.666367039317757 \tabularnewline
p-value & 0.552841417243748 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33203&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]98151.9153207162[/C][/ROW]
[ROW][C]beta[/C][C]-0.130226315834933[/C][/ROW]
[ROW][C]S.D.[/C][C]0.195427306801162[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.666367039317757[/C][/ROW]
[ROW][C]p-value[/C][C]0.552841417243748[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33203&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33203&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)
alpha98151.9153207162
beta-0.130226315834933
S.D.0.195427306801162
T-STAT-0.666367039317757
p-value0.552841417243748






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha49.7063564347729
beta-2.99672719634215
S.D.4.16527441038607
T-STAT-0.719454926875848
p-value0.523842118362622
Lambda3.99672719634215

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 49.7063564347729 \tabularnewline
beta & -2.99672719634215 \tabularnewline
S.D. & 4.16527441038607 \tabularnewline
T-STAT & -0.719454926875848 \tabularnewline
p-value & 0.523842118362622 \tabularnewline
Lambda & 3.99672719634215 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33203&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]49.7063564347729[/C][/ROW]
[ROW][C]beta[/C][C]-2.99672719634215[/C][/ROW]
[ROW][C]S.D.[/C][C]4.16527441038607[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.719454926875848[/C][/ROW]
[ROW][C]p-value[/C][C]0.523842118362622[/C][/ROW]
[ROW][C]Lambda[/C][C]3.99672719634215[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33203&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33203&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)
alpha49.7063564347729
beta-2.99672719634215
S.D.4.16527441038607
T-STAT-0.719454926875848
p-value0.523842118362622
Lambda3.99672719634215


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')