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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 computationSun, 20 Dec 2009 05:15:50 -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/20/t1261311436iavadyreblztx2a.htm/, Retrieved Sat, 27 Apr 2024 12:27:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69851, Retrieved Sat, 27 Apr 2024 12:27:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D          [Standard Deviation-Mean Plot] [Standaard Deviati...] [2009-12-20 12:15:50] [fe2edc5b0acc9545190e03904e9be55e] [Current]
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Dataseries X:
921365
987921
1132614
1332224
1418133
1411549
1695920
1636173
1539653
1395314
1127575
1036076
989236
1008380
1207763
1368839
1469798
1498721
1761769
1653214
1599104
1421179
1163995
1037735
1015407
1039210
1258049
1469445
1552346
1549144
1785895
1662335
1629440
1467430
1202209
1076982
1039367
1063449
1335135
1491602
1591972
1641248
1898849
1798580
1762444
1622044
1368955
1262973
1195650
1269530
1479279
1607819
1712466
1721766
1949843
1821326
1757802
1590367
1260647
1149235




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=69851&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=69851&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69851&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11302876.41666667257925.823408225774555
21348311.08333333263644.976474204772533
31392324.33333333263919.094020853770488
41489718.16666667280017.614230648859482
51542977.5268077.320340606800608

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1302876.41666667 & 257925.823408225 & 774555 \tabularnewline
2 & 1348311.08333333 & 263644.976474204 & 772533 \tabularnewline
3 & 1392324.33333333 & 263919.094020853 & 770488 \tabularnewline
4 & 1489718.16666667 & 280017.614230648 & 859482 \tabularnewline
5 & 1542977.5 & 268077.320340606 & 800608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69851&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]1302876.41666667[/C][C]257925.823408225[/C][C]774555[/C][/ROW]
[ROW][C]2[/C][C]1348311.08333333[/C][C]263644.976474204[/C][C]772533[/C][/ROW]
[ROW][C]3[/C][C]1392324.33333333[/C][C]263919.094020853[/C][C]770488[/C][/ROW]
[ROW][C]4[/C][C]1489718.16666667[/C][C]280017.614230648[/C][C]859482[/C][/ROW]
[ROW][C]5[/C][C]1542977.5[/C][C]268077.320340606[/C][C]800608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69851&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69851&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
11302876.41666667257925.823408225774555
21348311.08333333263644.976474204772533
31392324.33333333263919.094020853770488
41489718.16666667280017.614230648859482
51542977.5268077.320340606800608







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha179929.863078268
beta0.0613231753143467
S.D.0.0324534563651337
T-STAT1.88957301263693
p-value0.155219922798161

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 179929.863078268 \tabularnewline
beta & 0.0613231753143467 \tabularnewline
S.D. & 0.0324534563651337 \tabularnewline
T-STAT & 1.88957301263693 \tabularnewline
p-value & 0.155219922798161 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69851&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]179929.863078268[/C][/ROW]
[ROW][C]beta[/C][C]0.0613231753143467[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0324534563651337[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.88957301263693[/C][/ROW]
[ROW][C]p-value[/C][C]0.155219922798161[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69851&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69851&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)
alpha179929.863078268
beta0.0613231753143467
S.D.0.0324534563651337
T-STAT1.88957301263693
p-value0.155219922798161







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.82699750858175
beta0.329540007108763
S.D.0.167312452218385
T-STAT1.96960837486639
p-value0.143501572471863
Lambda0.670459992891237

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.82699750858175 \tabularnewline
beta & 0.329540007108763 \tabularnewline
S.D. & 0.167312452218385 \tabularnewline
T-STAT & 1.96960837486639 \tabularnewline
p-value & 0.143501572471863 \tabularnewline
Lambda & 0.670459992891237 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69851&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.82699750858175[/C][/ROW]
[ROW][C]beta[/C][C]0.329540007108763[/C][/ROW]
[ROW][C]S.D.[/C][C]0.167312452218385[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.96960837486639[/C][/ROW]
[ROW][C]p-value[/C][C]0.143501572471863[/C][/ROW]
[ROW][C]Lambda[/C][C]0.670459992891237[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69851&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69851&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)
alpha7.82699750858175
beta0.329540007108763
S.D.0.167312452218385
T-STAT1.96960837486639
p-value0.143501572471863
Lambda0.670459992891237



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')