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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, 19 Dec 2008 07:39:21 -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/19/t1229697793mrebq0m10dtn57f.htm/, Retrieved Wed, 15 May 2024 07:49:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35156, Retrieved Wed, 15 May 2024 07:49:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact218

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [Paper Arima Backw...] [2008-12-19 10:49:33] [f9b9e85820b2a54b20380c3265aca831]
- RMPD    [Standard Deviation-Mean Plot] [Paper H5 Vrouwen ...] [2008-12-19 14:39:21] [5e9e099b83e50415d7642e10d74756e4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
308347
298427
289231
291975
294912
293488
290555
284736
281818
287854
316263
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
301631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603

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=35156&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=35156&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35156&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
1296918.16666666713202.628270250743594
2316932.58333333312223.388954699937382
3314834.2513573.863174397837509
4289833.33333333318842.251937085664326
5266403.91666666713967.846527965143191

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 296918.166666667 & 13202.6282702507 & 43594 \tabularnewline
2 & 316932.583333333 & 12223.3889546999 & 37382 \tabularnewline
3 & 314834.25 & 13573.8631743978 & 37509 \tabularnewline
4 & 289833.333333333 & 18842.2519370856 & 64326 \tabularnewline
5 & 266403.916666667 & 13967.8465279651 & 43191 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35156&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]296918.166666667[/C][C]13202.6282702507[/C][C]43594[/C][/ROW]
[ROW][C]2[/C][C]316932.583333333[/C][C]12223.3889546999[/C][C]37382[/C][/ROW]
[ROW][C]3[/C][C]314834.25[/C][C]13573.8631743978[/C][C]37509[/C][/ROW]
[ROW][C]4[/C][C]289833.333333333[/C][C]18842.2519370856[/C][C]64326[/C][/ROW]
[ROW][C]5[/C][C]266403.916666667[/C][C]13967.8465279651[/C][C]43191[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35156&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35156&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
1296918.16666666713202.628270250743594
2316932.58333333312223.388954699937382
3314834.2513573.863174397837509
4289833.33333333318842.251937085664326
5266403.91666666713967.846527965143191






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha27727.9406378576
beta-0.0450055377141051
S.D.0.067560786214614
T-STAT-0.666148815544275
p-value0.552963145973807

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 27727.9406378576 \tabularnewline
beta & -0.0450055377141051 \tabularnewline
S.D. & 0.067560786214614 \tabularnewline
T-STAT & -0.666148815544275 \tabularnewline
p-value & 0.552963145973807 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35156&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]27727.9406378576[/C][/ROW]
[ROW][C]beta[/C][C]-0.0450055377141051[/C][/ROW]
[ROW][C]S.D.[/C][C]0.067560786214614[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.666148815544275[/C][/ROW]
[ROW][C]p-value[/C][C]0.552963145973807[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35156&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35156&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)
alpha27727.9406378576
beta-0.0450055377141051
S.D.0.067560786214614
T-STAT-0.666148815544275
p-value0.552963145973807






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha20.5551905676487
beta-0.87261539453967
S.D.1.25677902004269
T-STAT-0.694326831227679
p-value0.537415541313624
Lambda1.87261539453967

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 20.5551905676487 \tabularnewline
beta & -0.87261539453967 \tabularnewline
S.D. & 1.25677902004269 \tabularnewline
T-STAT & -0.694326831227679 \tabularnewline
p-value & 0.537415541313624 \tabularnewline
Lambda & 1.87261539453967 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35156&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]20.5551905676487[/C][/ROW]
[ROW][C]beta[/C][C]-0.87261539453967[/C][/ROW]
[ROW][C]S.D.[/C][C]1.25677902004269[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.694326831227679[/C][/ROW]
[ROW][C]p-value[/C][C]0.537415541313624[/C][/ROW]
[ROW][C]Lambda[/C][C]1.87261539453967[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35156&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35156&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)
alpha20.5551905676487
beta-0.87261539453967
S.D.1.25677902004269
T-STAT-0.694326831227679
p-value0.537415541313624
Lambda1.87261539453967


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')