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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, 06 Dec 2008 04:36:39 -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/06/t1228563649bzj6muaco7ynfz6.htm/, Retrieved Fri, 17 May 2024 05:14:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29516, Retrieved Fri, 17 May 2024 05:14:11 +0000
QR Codes:

Original text written by user:Reeks: werkloosheid tussen 25 en -50 Tijd: 31/1/2003 - 31/12/2007
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact260

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]
- RMPD      [Standard Deviation-Mean Plot] [SD mean plot] [2008-12-06 11:36:39] [9b05d7ef5dbcfba4217d280d9092f628] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
354846
356427
353467
355996
352487
355178
374556
375021
375787
372720
364431
370490
376974
377632
378205
370861
369167
371551
382842
381903
384502
392058
384359
388884
386586
387495
385705
378670
377367
376911
389827
387820
387267
380575
372402
376740
377795
376126
370804
367980
367866
366121
379421
378519
372423
355072
344693
342892
344178
337606
327103
323953
316532
306307
327225
329573
313761
307836
300074
304198

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=29516&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=29516&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29516&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
1363450.59596.764639473823300
2379911.57169.6394419296122891
3382280.4166666675777.3602096826417425
4366642.66666666712622.813750099336529
5319862.16666666713939.488335681744104

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 363450.5 & 9596.7646394738 & 23300 \tabularnewline
2 & 379911.5 & 7169.63944192961 & 22891 \tabularnewline
3 & 382280.416666667 & 5777.36020968264 & 17425 \tabularnewline
4 & 366642.666666667 & 12622.8137500993 & 36529 \tabularnewline
5 & 319862.166666667 & 13939.4883356817 & 44104 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29516&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]363450.5[/C][C]9596.7646394738[/C][C]23300[/C][/ROW]
[ROW][C]2[/C][C]379911.5[/C][C]7169.63944192961[/C][C]22891[/C][/ROW]
[ROW][C]3[/C][C]382280.416666667[/C][C]5777.36020968264[/C][C]17425[/C][/ROW]
[ROW][C]4[/C][C]366642.666666667[/C][C]12622.8137500993[/C][C]36529[/C][/ROW]
[ROW][C]5[/C][C]319862.166666667[/C][C]13939.4883356817[/C][C]44104[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29516&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29516&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
1363450.59596.764639473823300
2379911.57169.6394419296122891
3382280.4166666675777.3602096826417425
4366642.66666666712622.813750099336529
5319862.16666666713939.488335681744104






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha51408.4704232949
beta-0.114745799900978
S.D.0.0443412386118654
T-STAT-2.58778968502411
p-value0.081229412904488

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 51408.4704232949 \tabularnewline
beta & -0.114745799900978 \tabularnewline
S.D. & 0.0443412386118654 \tabularnewline
T-STAT & -2.58778968502411 \tabularnewline
p-value & 0.081229412904488 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29516&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]51408.4704232949[/C][/ROW]
[ROW][C]beta[/C][C]-0.114745799900978[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0443412386118654[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.58778968502411[/C][/ROW]
[ROW][C]p-value[/C][C]0.081229412904488[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29516&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29516&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)
alpha51408.4704232949
beta-0.114745799900978
S.D.0.0443412386118654
T-STAT-2.58778968502411
p-value0.081229412904488






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha61.1958915410597
beta-4.06741479774023
S.D.1.82783837130285
T-STAT-2.22525955336031
p-value0.112491247478729
Lambda5.06741479774023

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 61.1958915410597 \tabularnewline
beta & -4.06741479774023 \tabularnewline
S.D. & 1.82783837130285 \tabularnewline
T-STAT & -2.22525955336031 \tabularnewline
p-value & 0.112491247478729 \tabularnewline
Lambda & 5.06741479774023 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29516&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]61.1958915410597[/C][/ROW]
[ROW][C]beta[/C][C]-4.06741479774023[/C][/ROW]
[ROW][C]S.D.[/C][C]1.82783837130285[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.22525955336031[/C][/ROW]
[ROW][C]p-value[/C][C]0.112491247478729[/C][/ROW]
[ROW][C]Lambda[/C][C]5.06741479774023[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29516&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29516&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)
alpha61.1958915410597
beta-4.06741479774023
S.D.1.82783837130285
T-STAT-2.22525955336031
p-value0.112491247478729
Lambda5.06741479774023


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')