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Description of Statistical Computation

Author's title

Standard Deviation-Mean plot Totaal # niet-werkende werkzoekende mannen in ...

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 07:09:03 -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/t1229177645ji3svxetkbtczin.htm/, Retrieved Sat, 18 May 2024 10:37:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33110, Retrieved Sat, 18 May 2024 10:37:40 +0000
QR Codes:

Original text written by user:Seizoenale periode = 12
IsPrivate?No (this computation is public)
User-defined keywordsStandard Deviation-Mean plot Totaal niet-werkende werkzoekende mannen Vlaams gewest
Estimated Impact157

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-12-13 14:09:03] [f4b2017b314c03698059f43b95818e67] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106099
103235
98857
101107
102700
101477
99639
96622
94697
95093
112885
121162
113624
111632
106707
108827
108413
106249
104861
102382
100320
100228
117089
121523
114948
112831
107605
108928
101993
102850
99925
101536
99450
98305
110159
109483
106810
96279
91982
90276
90999
86622
83117
80367
77550
77443
92844
92175
84822
81632
78872
81485
80651
78192
76844
76335
71415
73899
86822
86371
83469
82662

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=33110&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=33110&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33110&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
1102797.757647.5351005167926465
2108487.9166666676563.2549776399221295
3105667.755648.0838122322516643
4888728468.2122509578629367
579778.33333333334804.7520101237215407

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102797.75 & 7647.53510051679 & 26465 \tabularnewline
2 & 108487.916666667 & 6563.25497763992 & 21295 \tabularnewline
3 & 105667.75 & 5648.08381223225 & 16643 \tabularnewline
4 & 88872 & 8468.21225095786 & 29367 \tabularnewline
5 & 79778.3333333333 & 4804.75201012372 & 15407 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33110&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]102797.75[/C][C]7647.53510051679[/C][C]26465[/C][/ROW]
[ROW][C]2[/C][C]108487.916666667[/C][C]6563.25497763992[/C][C]21295[/C][/ROW]
[ROW][C]3[/C][C]105667.75[/C][C]5648.08381223225[/C][C]16643[/C][/ROW]
[ROW][C]4[/C][C]88872[/C][C]8468.21225095786[/C][C]29367[/C][/ROW]
[ROW][C]5[/C][C]79778.3333333333[/C][C]4804.75201012372[/C][C]15407[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33110&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33110&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
1102797.757647.5351005167926465
2108487.9166666676563.2549776399221295
3105667.755648.0838122322516643
4888728468.2122509578629367
579778.33333333334804.7520101237215407






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4514.79049014693
beta0.0217417713531576
S.D.0.0682450095753485
T-STAT0.318584047221105
p-value0.770933524860262

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4514.79049014693 \tabularnewline
beta & 0.0217417713531576 \tabularnewline
S.D. & 0.0682450095753485 \tabularnewline
T-STAT & 0.318584047221105 \tabularnewline
p-value & 0.770933524860262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33110&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4514.79049014693[/C][/ROW]
[ROW][C]beta[/C][C]0.0217417713531576[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0682450095753485[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.318584047221105[/C][/ROW]
[ROW][C]p-value[/C][C]0.770933524860262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33110&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33110&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)
alpha4514.79049014693
beta0.0217417713531576
S.D.0.0682450095753485
T-STAT0.318584047221105
p-value0.770933524860262






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.05387183553538
beta0.49878129521913
S.D.0.959504821713108
T-STAT0.519831984094256
p-value0.63910229674829
Lambda0.50121870478087

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.05387183553538 \tabularnewline
beta & 0.49878129521913 \tabularnewline
S.D. & 0.959504821713108 \tabularnewline
T-STAT & 0.519831984094256 \tabularnewline
p-value & 0.63910229674829 \tabularnewline
Lambda & 0.50121870478087 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33110&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.05387183553538[/C][/ROW]
[ROW][C]beta[/C][C]0.49878129521913[/C][/ROW]
[ROW][C]S.D.[/C][C]0.959504821713108[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.519831984094256[/C][/ROW]
[ROW][C]p-value[/C][C]0.63910229674829[/C][/ROW]
[ROW][C]Lambda[/C][C]0.50121870478087[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33110&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33110&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)
alpha3.05387183553538
beta0.49878129521913
S.D.0.959504821713108
T-STAT0.519831984094256
p-value0.63910229674829
Lambda0.50121870478087


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')