Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 22 Nov 2007 06:59:15 -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/2007/Nov/22/t11957394787opmi6v20h65vvm.htm/, Retrieved Thu, 02 May 2024 16:39:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5998, Retrieved Thu, 02 May 2024 16:39:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [SDMP P-index ener...] [2007-11-22 13:59:15] [4df98167d5cf79c69ce763f2d4ef5b15] [Current]
Feedback Forum

Post a new message
Dataseries X:
96,8
87,0
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
110,3
109,8
117,3
118,8
131,3
125,9
133,1
147,0
145,8
164,4
149,8
137,7
151,7
156,8
180,0
180,4
170,4
191,6
199,5
218,2
217,5
205,0
194,0
199,3
219,3
211,1
215,2
240,2
242,2
240,7
255,4
253,0
218,2
203,7
205,6
215,6
188,5
202,9
214,0
230,3
230,0
241,0
259,6
247,8
270,3




Summary of compuational 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 compuational 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=5998&T=0

[TABLE]
[ROW][C]Summary of compuational 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=5998&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5998&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 compuational 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
198.90833333333338.194949479386518.4
2120.74166666666715.904799637692860
3176.526.301469022229121.9
4224.46666666666721.0358712390972148.3
5225.77525.1016886429434160.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 98.9083333333333 & 8.1949494793865 & 18.4 \tabularnewline
2 & 120.741666666667 & 15.9047996376928 & 60 \tabularnewline
3 & 176.5 & 26.301469022229 & 121.9 \tabularnewline
4 & 224.466666666667 & 21.0358712390972 & 148.3 \tabularnewline
5 & 225.775 & 25.1016886429434 & 160.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5998&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]98.9083333333333[/C][C]8.1949494793865[/C][C]18.4[/C][/ROW]
[ROW][C]2[/C][C]120.741666666667[/C][C]15.9047996376928[/C][C]60[/C][/ROW]
[ROW][C]3[/C][C]176.5[/C][C]26.301469022229[/C][C]121.9[/C][/ROW]
[ROW][C]4[/C][C]224.466666666667[/C][C]21.0358712390972[/C][C]148.3[/C][/ROW]
[ROW][C]5[/C][C]225.775[/C][C]25.1016886429434[/C][C]160.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5998&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5998&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
198.90833333333338.194949479386518.4
2120.74166666666715.904799637692860
3176.526.301469022229121.9
4224.46666666666721.0358712390972148.3
5225.77525.1016886429434160.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.6250023945911
beta0.104459636750196
S.D.0.0420614991565137
T-STAT2.48349770799883
p-value0.0889941123297296

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.6250023945911 \tabularnewline
beta & 0.104459636750196 \tabularnewline
S.D. & 0.0420614991565137 \tabularnewline
T-STAT & 2.48349770799883 \tabularnewline
p-value & 0.0889941123297296 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5998&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.6250023945911[/C][/ROW]
[ROW][C]beta[/C][C]0.104459636750196[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0420614991565137[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.48349770799883[/C][/ROW]
[ROW][C]p-value[/C][C]0.0889941123297296[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5998&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5998&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)
alpha1.6250023945911
beta0.104459636750196
S.D.0.0420614991565137
T-STAT2.48349770799883
p-value0.0889941123297296







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.79005956943702
beta1.11674968225306
S.D.0.366253878666631
T-STAT3.04911359933893
p-value0.055466776787875
Lambda-0.116749682253056

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.79005956943702 \tabularnewline
beta & 1.11674968225306 \tabularnewline
S.D. & 0.366253878666631 \tabularnewline
T-STAT & 3.04911359933893 \tabularnewline
p-value & 0.055466776787875 \tabularnewline
Lambda & -0.116749682253056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5998&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.79005956943702[/C][/ROW]
[ROW][C]beta[/C][C]1.11674968225306[/C][/ROW]
[ROW][C]S.D.[/C][C]0.366253878666631[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.04911359933893[/C][/ROW]
[ROW][C]p-value[/C][C]0.055466776787875[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.116749682253056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5998&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5998&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)
alpha-2.79005956943702
beta1.11674968225306
S.D.0.366253878666631
T-STAT3.04911359933893
p-value0.055466776787875
Lambda-0.116749682253056



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')