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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, 05 Dec 2008 05:27:58 -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/2008/Dec/05/t1228480109qe1iu50dltwntlj.htm/, Retrieved Thu, 16 May 2024 20:41:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29213, Retrieved Thu, 16 May 2024 20:41:17 +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)
-     [Univariate Data Series] [Werkloosheid totalen] [2008-11-28 13:18:02] [6743688719638b0cb1c0a6e0bf433315]
-   P   [Univariate Data Series] [Total unemployment] [2008-12-02 17:54:00] [6743688719638b0cb1c0a6e0bf433315]
- RMP       [Standard Deviation-Mean Plot] [total unemployment] [2008-12-05 12:27:58] [9b05d7ef5dbcfba4217d280d9092f628] [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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29213&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29213&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29213&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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=29213&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=29213&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29213&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)
alpha98151.915320716
beta-0.130226315834933
S.D.0.195427306801162
T-STAT-0.666367039317755
p-value0.552841417243749

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 98151.915320716 \tabularnewline
beta & -0.130226315834933 \tabularnewline
S.D. & 0.195427306801162 \tabularnewline
T-STAT & -0.666367039317755 \tabularnewline
p-value & 0.552841417243749 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29213&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]98151.915320716[/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]-0.666367039317755[/C][/ROW]
[ROW][C]p-value[/C][C]0.552841417243749[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29213&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29213&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)
alpha98151.915320716
beta-0.130226315834933
S.D.0.195427306801162
T-STAT-0.666367039317755
p-value0.552841417243749






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha49.7063564347743
beta-2.99672719634225
S.D.4.16527441038607
T-STAT-0.719454926875872
p-value0.523842118362609
Lambda3.99672719634225

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 49.7063564347743 \tabularnewline
beta & -2.99672719634225 \tabularnewline
S.D. & 4.16527441038607 \tabularnewline
T-STAT & -0.719454926875872 \tabularnewline
p-value & 0.523842118362609 \tabularnewline
Lambda & 3.99672719634225 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29213&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]49.7063564347743[/C][/ROW]
[ROW][C]beta[/C][C]-2.99672719634225[/C][/ROW]
[ROW][C]S.D.[/C][C]4.16527441038607[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.719454926875872[/C][/ROW]
[ROW][C]p-value[/C][C]0.523842118362609[/C][/ROW]
[ROW][C]Lambda[/C][C]3.99672719634225[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29213&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29213&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)
alpha49.7063564347743
beta-2.99672719634225
S.D.4.16527441038607
T-STAT-0.719454926875872
p-value0.523842118362609
Lambda3.99672719634225


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Unemployment between 25 and -50 ; par2 = http://www.nbb.be/belgostat/PresentationLinker?TableId=217000022&Lang=N ; par3 = Unemployment between 25 and -50 ;
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')