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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 computationSun, 19 Dec 2010 16:35:52 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t1292776418bdpk475hptgmf24.htm/, Retrieved Sat, 04 May 2024 20:59:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112597, Retrieved Sat, 04 May 2024 20:59:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [WS7] [2009-11-18 17:01:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Multiple Regression] [WS7(2)] [2009-11-20 19:01:46] [7d268329e554b8694908ba13e6e6f258]
-   P         [Multiple Regression] [WS7(3)] [2009-11-21 10:22:47] [7d268329e554b8694908ba13e6e6f258]
-   PD          [Multiple Regression] [WS7(4)] [2009-11-21 10:55:20] [7d268329e554b8694908ba13e6e6f258]
- RMPD            [Univariate Data Series] [Niet-werkende wer...] [2009-11-25 19:16:52] [9717cb857c153ca3061376906953b329]
-   PD              [Univariate Data Series] [] [2010-12-16 17:58:43] [bcc4ad4a6c0f95d5b548de29638ac6c2]
-   PD                [Univariate Data Series] [] [2010-12-19 14:40:10] [bcc4ad4a6c0f95d5b548de29638ac6c2]
- RMP                     [Standard Deviation-Mean Plot] [] [2010-12-19 16:35:52] [4e3652732e77bb1a104cdb5f8d687d01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
528222
532638
536322
536535
523597
536214
586570
596594
580523
564478
557560
575093
580112
574761
563250
551531
537034
544686
600991
604378
586111
563668
548604

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=112597&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=112597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112597&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
1576612.08333333329164.685309021375951
2596397.41666666721872.304573502661428
3588261.16666666722629.620286989668535
4532458.83333333321778.072975246365929
550486519560.160730888264233
6554528.83333333325444.42511483172997

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 576612.083333333 & 29164.6853090213 & 75951 \tabularnewline
2 & 596397.416666667 & 21872.3045735026 & 61428 \tabularnewline
3 & 588261.166666667 & 22629.6202869896 & 68535 \tabularnewline
4 & 532458.833333333 & 21778.0729752463 & 65929 \tabularnewline
5 & 504865 & 19560.1607308882 & 64233 \tabularnewline
6 & 554528.833333333 & 25444.425114831 & 72997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112597&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]576612.083333333[/C][C]29164.6853090213[/C][C]75951[/C][/ROW]
[ROW][C]2[/C][C]596397.416666667[/C][C]21872.3045735026[/C][C]61428[/C][/ROW]
[ROW][C]3[/C][C]588261.166666667[/C][C]22629.6202869896[/C][C]68535[/C][/ROW]
[ROW][C]4[/C][C]532458.833333333[/C][C]21778.0729752463[/C][C]65929[/C][/ROW]
[ROW][C]5[/C][C]504865[/C][C]19560.1607308882[/C][C]64233[/C][/ROW]
[ROW][C]6[/C][C]554528.833333333[/C][C]25444.425114831[/C][C]72997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112597&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
1576612.08333333329164.685309021375951
2596397.41666666721872.304573502661428
3588261.16666666722629.620286989668535
4532458.83333333321778.072975246365929
550486519560.160730888264233
6554528.83333333325444.42511483172997






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-279.611658815008
beta0.0423864334277501
S.D.0.0432499906139386
T-STAT0.980033355523777
p-value0.382558948805661

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -279.611658815008 \tabularnewline
beta & 0.0423864334277501 \tabularnewline
S.D. & 0.0432499906139386 \tabularnewline
T-STAT & 0.980033355523777 \tabularnewline
p-value & 0.382558948805661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112597&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-279.611658815008[/C][/ROW]
[ROW][C]beta[/C][C]0.0423864334277501[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0432499906139386[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.980033355523777[/C][/ROW]
[ROW][C]p-value[/C][C]0.382558948805661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112597&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112597&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)
alpha-279.611658815008
beta0.0423864334277501
S.D.0.0432499906139386
T-STAT0.980033355523777
p-value0.382558948805661






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.94860975806462
beta1.05812736107085
S.D.0.95599503453325
T-STAT1.10683353244346
p-value0.330446134610714
Lambda-0.0581273610708466

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.94860975806462 \tabularnewline
beta & 1.05812736107085 \tabularnewline
S.D. & 0.95599503453325 \tabularnewline
T-STAT & 1.10683353244346 \tabularnewline
p-value & 0.330446134610714 \tabularnewline
Lambda & -0.0581273610708466 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112597&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.94860975806462[/C][/ROW]
[ROW][C]beta[/C][C]1.05812736107085[/C][/ROW]
[ROW][C]S.D.[/C][C]0.95599503453325[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.10683353244346[/C][/ROW]
[ROW][C]p-value[/C][C]0.330446134610714[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0581273610708466[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112597&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112597&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)
alpha-3.94860975806462
beta1.05812736107085
S.D.0.95599503453325
T-STAT1.10683353244346
p-value0.330446134610714
Lambda-0.0581273610708466


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Niet-werkende werkzoekenden in Belgie ; par2 = http://www.nbb.be/belgostat/ ; par3 = Niet-werkende werkzoekenden in Belgie ; par4 = 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')