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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, 04 Dec 2009 06:08:57 -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/2009/Dec/04/t1259932174qhmnkt5onwdy6kg.htm/, Retrieved Sat, 27 Apr 2024 14:37:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63459, Retrieved Sat, 27 Apr 2024 14:37:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D      [Standard Deviation-Mean Plot] [] [2009-12-04 13:08:57] [54e293c1fb7c46e2abc5c1dda68d8adb] [Current]
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Dataseries X:
274412
272433
268361
268586
264768
269974
304744
309365
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
260376
263903
264291
263276
262572
256167
264221
293860




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63459&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63459&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63459&T=0

As an alternative you can also use a 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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1285051.91666666717127.305660092744597
2305362.517897.157349194346464
3316846.16666666712991.324201756837382
4309483.33333333314323.664534502743670
5279244.513386.150634823440308
6262323.33333333312149.093272064941454

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 285051.916666667 & 17127.3056600927 & 44597 \tabularnewline
2 & 305362.5 & 17897.1573491943 & 46464 \tabularnewline
3 & 316846.166666667 & 12991.3242017568 & 37382 \tabularnewline
4 & 309483.333333333 & 14323.6645345027 & 43670 \tabularnewline
5 & 279244.5 & 13386.1506348234 & 40308 \tabularnewline
6 & 262323.333333333 & 12149.0932720649 & 41454 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63459&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]285051.916666667[/C][C]17127.3056600927[/C][C]44597[/C][/ROW]
[ROW][C]2[/C][C]305362.5[/C][C]17897.1573491943[/C][C]46464[/C][/ROW]
[ROW][C]3[/C][C]316846.166666667[/C][C]12991.3242017568[/C][C]37382[/C][/ROW]
[ROW][C]4[/C][C]309483.333333333[/C][C]14323.6645345027[/C][C]43670[/C][/ROW]
[ROW][C]5[/C][C]279244.5[/C][C]13386.1506348234[/C][C]40308[/C][/ROW]
[ROW][C]6[/C][C]262323.333333333[/C][C]12149.0932720649[/C][C]41454[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63459&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63459&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1285051.91666666717127.305660092744597
2305362.517897.157349194346464
3316846.16666666712991.324201756837382
4309483.33333333314323.664534502743670
5279244.513386.150634823440308
6262323.33333333312149.093272064941454







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5314.28924144672
beta0.0318424535374653
S.D.0.0536483875865895
T-STAT0.5935398055733
p-value0.584755901182081

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5314.28924144672 \tabularnewline
beta & 0.0318424535374653 \tabularnewline
S.D. & 0.0536483875865895 \tabularnewline
T-STAT & 0.5935398055733 \tabularnewline
p-value & 0.584755901182081 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63459&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5314.28924144672[/C][/ROW]
[ROW][C]beta[/C][C]0.0318424535374653[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0536483875865895[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.5935398055733[/C][/ROW]
[ROW][C]p-value[/C][C]0.584755901182081[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63459&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63459&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5314.28924144672
beta0.0318424535374653
S.D.0.0536483875865895
T-STAT0.5935398055733
p-value0.584755901182081







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.778544514350695
beta0.699434134937642
S.D.1.02255027207730
T-STAT0.684009533845945
p-value0.53153977736383
Lambda0.300565865062358

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.778544514350695 \tabularnewline
beta & 0.699434134937642 \tabularnewline
S.D. & 1.02255027207730 \tabularnewline
T-STAT & 0.684009533845945 \tabularnewline
p-value & 0.53153977736383 \tabularnewline
Lambda & 0.300565865062358 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63459&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.778544514350695[/C][/ROW]
[ROW][C]beta[/C][C]0.699434134937642[/C][/ROW]
[ROW][C]S.D.[/C][C]1.02255027207730[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.684009533845945[/C][/ROW]
[ROW][C]p-value[/C][C]0.53153977736383[/C][/ROW]
[ROW][C]Lambda[/C][C]0.300565865062358[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63459&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63459&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.778544514350695
beta0.699434134937642
S.D.1.02255027207730
T-STAT0.684009533845945
p-value0.53153977736383
Lambda0.300565865062358



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')