Free Statistics

of Irreproducible Research!

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, 27 Nov 2009 14:46:12 -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/Nov/27/t1259358450x91z0hvxfvql9yf.htm/, Retrieved Sun, 28 Apr 2024 20:33:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61300, Retrieved Sun, 28 Apr 2024 20:33:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
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] [WS8 Identifying I...] [2009-11-27 21:46:12] [c6e373ff11c42d4585d53e9e88ed5606] [Current]
Feedback Forum

Post a new message
Dataseries X:
7.1
6.9
6.8
7.5
7.6
7.8
8.0
8.1
8.2
8.3
8.2
8.0
7.9
7.6
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.0
8.2
8.1
8.1
8.0
7.9
7.9
8.0
8.0
7.9
8.0
7.7
7.2
7.5
7.3
7.0
7.0
7.0
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8.0
8.0
7.7
7.3
7.4
8.1
8.3
8.2




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=61300&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=61300&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61300&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
17.708333333333330.5282188481256151.5
28.30.413411527305531.3
38.358333333333330.688157399190482.1
48.466666666666670.2674231693686080.799999999999999
58.0750.1815338686155990.6
67.258333333333330.3369875458538581.2
77.183333333333330.689971453076581.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.70833333333333 & 0.528218848125615 & 1.5 \tabularnewline
2 & 8.3 & 0.41341152730553 & 1.3 \tabularnewline
3 & 8.35833333333333 & 0.68815739919048 & 2.1 \tabularnewline
4 & 8.46666666666667 & 0.267423169368608 & 0.799999999999999 \tabularnewline
5 & 8.075 & 0.181533868615599 & 0.6 \tabularnewline
6 & 7.25833333333333 & 0.336987545853858 & 1.2 \tabularnewline
7 & 7.18333333333333 & 0.68997145307658 & 1.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61300&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]7.70833333333333[/C][C]0.528218848125615[/C][C]1.5[/C][/ROW]
[ROW][C]2[/C][C]8.3[/C][C]0.41341152730553[/C][C]1.3[/C][/ROW]
[ROW][C]3[/C][C]8.35833333333333[/C][C]0.68815739919048[/C][C]2.1[/C][/ROW]
[ROW][C]4[/C][C]8.46666666666667[/C][C]0.267423169368608[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]5[/C][C]8.075[/C][C]0.181533868615599[/C][C]0.6[/C][/ROW]
[ROW][C]6[/C][C]7.25833333333333[/C][C]0.336987545853858[/C][C]1.2[/C][/ROW]
[ROW][C]7[/C][C]7.18333333333333[/C][C]0.68997145307658[/C][C]1.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61300&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61300&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
17.708333333333330.5282188481256151.5
28.30.413411527305531.3
38.358333333333330.688157399190482.1
48.466666666666670.2674231693686080.799999999999999
58.0750.1815338686155990.6
67.258333333333330.3369875458538581.2
77.183333333333330.689971453076581.9







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.24240493224281
beta-0.101014105043602
S.D.0.162574812447674
T-STAT-0.621339206995023
p-value0.561604064169746

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.24240493224281 \tabularnewline
beta & -0.101014105043602 \tabularnewline
S.D. & 0.162574812447674 \tabularnewline
T-STAT & -0.621339206995023 \tabularnewline
p-value & 0.561604064169746 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61300&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.24240493224281[/C][/ROW]
[ROW][C]beta[/C][C]-0.101014105043602[/C][/ROW]
[ROW][C]S.D.[/C][C]0.162574812447674[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.621339206995023[/C][/ROW]
[ROW][C]p-value[/C][C]0.561604064169746[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61300&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61300&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)
alpha1.24240493224281
beta-0.101014105043602
S.D.0.162574812447674
T-STAT-0.621339206995023
p-value0.561604064169746







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.34424224876176
beta-2.06000840889206
S.D.3.14179480307168
T-STAT-0.655678851743605
p-value0.540996626527415
Lambda3.06000840889206

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.34424224876176 \tabularnewline
beta & -2.06000840889206 \tabularnewline
S.D. & 3.14179480307168 \tabularnewline
T-STAT & -0.655678851743605 \tabularnewline
p-value & 0.540996626527415 \tabularnewline
Lambda & 3.06000840889206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61300&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.34424224876176[/C][/ROW]
[ROW][C]beta[/C][C]-2.06000840889206[/C][/ROW]
[ROW][C]S.D.[/C][C]3.14179480307168[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.655678851743605[/C][/ROW]
[ROW][C]p-value[/C][C]0.540996626527415[/C][/ROW]
[ROW][C]Lambda[/C][C]3.06000840889206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61300&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61300&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)
alpha3.34424224876176
beta-2.06000840889206
S.D.3.14179480307168
T-STAT-0.655678851743605
p-value0.540996626527415
Lambda3.06000840889206



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')