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 computationTue, 01 Dec 2009 09:12:51 -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/01/t12596840545ca7v1y7deed88v.htm/, Retrieved Fri, 29 Mar 2024 14:15:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62108, Retrieved Fri, 29 Mar 2024 14:15:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
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] [] [2009-11-27 12:56:20] [7e8bf94ac9834384fa22d029eca19fa6]
-    D            [Standard Deviation-Mean Plot] [] [2009-12-01 16:12:51] [4f23cd6f600e6b4b5336072a0ca6bd10] [Current]
Feedback Forum

Post a new message
Dataseries X:
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
8,2
8,1
8,1
8
7,9
7,9
8
8
7,9
8
7,7
7,2
7,5
7,3
7
7
7
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
8
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=62108&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=62108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62108&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
18.416666666666670.2691175253012010.799999999999999
28.383333333333330.2405801069888940.700
37.70.3592922335521731
47.041666666666670.5333570070503411.8
57.591666666666670.5680242205676751.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.41666666666667 & 0.269117525301201 & 0.799999999999999 \tabularnewline
2 & 8.38333333333333 & 0.240580106988894 & 0.700 \tabularnewline
3 & 7.7 & 0.359292233552173 & 1 \tabularnewline
4 & 7.04166666666667 & 0.533357007050341 & 1.8 \tabularnewline
5 & 7.59166666666667 & 0.568024220567675 & 1.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62108&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]8.41666666666667[/C][C]0.269117525301201[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]2[/C][C]8.38333333333333[/C][C]0.240580106988894[/C][C]0.700[/C][/ROW]
[ROW][C]3[/C][C]7.7[/C][C]0.359292233552173[/C][C]1[/C][/ROW]
[ROW][C]4[/C][C]7.04166666666667[/C][C]0.533357007050341[/C][C]1.8[/C][/ROW]
[ROW][C]5[/C][C]7.59166666666667[/C][C]0.568024220567675[/C][C]1.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62108&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
18.416666666666670.2691175253012010.799999999999999
28.383333333333330.2405801069888940.700
37.70.3592922335521731
47.041666666666670.5333570070503411.8
57.591666666666670.5680242205676751.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.16814962198531
beta-0.226670622226565
S.D.0.071979580175025
T-STAT-3.14909619749649
p-value0.0513012149612681

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.16814962198531 \tabularnewline
beta & -0.226670622226565 \tabularnewline
S.D. & 0.071979580175025 \tabularnewline
T-STAT & -3.14909619749649 \tabularnewline
p-value & 0.0513012149612681 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62108&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.16814962198531[/C][/ROW]
[ROW][C]beta[/C][C]-0.226670622226565[/C][/ROW]
[ROW][C]S.D.[/C][C]0.071979580175025[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.14909619749649[/C][/ROW]
[ROW][C]p-value[/C][C]0.0513012149612681[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62108&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62108&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)
alpha2.16814962198531
beta-0.226670622226565
S.D.0.071979580175025
T-STAT-3.14909619749649
p-value0.0513012149612681







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha8.56746392315155
beta-4.65061556458141
S.D.1.34713995473829
T-STAT-3.4522141134808
p-value0.0408707964943855
Lambda5.6506155645814

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 8.56746392315155 \tabularnewline
beta & -4.65061556458141 \tabularnewline
S.D. & 1.34713995473829 \tabularnewline
T-STAT & -3.4522141134808 \tabularnewline
p-value & 0.0408707964943855 \tabularnewline
Lambda & 5.6506155645814 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62108&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.56746392315155[/C][/ROW]
[ROW][C]beta[/C][C]-4.65061556458141[/C][/ROW]
[ROW][C]S.D.[/C][C]1.34713995473829[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.4522141134808[/C][/ROW]
[ROW][C]p-value[/C][C]0.0408707964943855[/C][/ROW]
[ROW][C]Lambda[/C][C]5.6506155645814[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62108&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62108&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)
alpha8.56746392315155
beta-4.65061556458141
S.D.1.34713995473829
T-STAT-3.4522141134808
p-value0.0408707964943855
Lambda5.6506155645814



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')