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 computationWed, 02 Dec 2009 01:26:10 -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/02/t125974294396cokv7q84emcw7.htm/, Retrieved Sun, 28 Apr 2024 00:31:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62291, Retrieved Sun, 28 Apr 2024 00:31:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact198
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] [] [2009-12-02 08:26:10] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
Dataseries X:
1.7
2.4
2.0
2.1
2.0
1.8
2.7
2.3
1.9
2.0
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3.0
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2.0
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5
4.8
3.2
2.7
2.1
1.9
0.6




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=62291&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=62291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62291&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
12.166666666666670.3420083288016491.1
22.591666666666670.2906367096044420.8
32.133333333333330.3773913650631691.1
42.333333333333331.120335447601083.2
53.9251.777702807762675.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.16666666666667 & 0.342008328801649 & 1.1 \tabularnewline
2 & 2.59166666666667 & 0.290636709604442 & 0.8 \tabularnewline
3 & 2.13333333333333 & 0.377391365063169 & 1.1 \tabularnewline
4 & 2.33333333333333 & 1.12033544760108 & 3.2 \tabularnewline
5 & 3.925 & 1.77770280776267 & 5.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62291&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]2.16666666666667[/C][C]0.342008328801649[/C][C]1.1[/C][/ROW]
[ROW][C]2[/C][C]2.59166666666667[/C][C]0.290636709604442[/C][C]0.8[/C][/ROW]
[ROW][C]3[/C][C]2.13333333333333[/C][C]0.377391365063169[/C][C]1.1[/C][/ROW]
[ROW][C]4[/C][C]2.33333333333333[/C][C]1.12033544760108[/C][C]3.2[/C][/ROW]
[ROW][C]5[/C][C]3.925[/C][C]1.77770280776267[/C][C]5.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62291&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
12.166666666666670.3420083288016491.1
22.591666666666670.2906367096044420.8
32.133333333333330.3773913650631691.1
42.333333333333331.120335447601083.2
53.9251.777702807762675.3







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.12220387978346
beta0.723885479676831
S.D.0.283509596360367
T-STAT2.55330150714442
p-value0.0837014271988188

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.12220387978346 \tabularnewline
beta & 0.723885479676831 \tabularnewline
S.D. & 0.283509596360367 \tabularnewline
T-STAT & 2.55330150714442 \tabularnewline
p-value & 0.0837014271988188 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62291&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.12220387978346[/C][/ROW]
[ROW][C]beta[/C][C]0.723885479676831[/C][/ROW]
[ROW][C]S.D.[/C][C]0.283509596360367[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.55330150714442[/C][/ROW]
[ROW][C]p-value[/C][C]0.0837014271988188[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62291&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62291&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)
alpha-1.12220387978346
beta0.723885479676831
S.D.0.283509596360367
T-STAT2.55330150714442
p-value0.0837014271988188







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.6612895344685
beta2.28026532432789
S.D.1.31670662669902
T-STAT1.73179452285777
p-value0.181737219841521
Lambda-1.28026532432789

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.6612895344685 \tabularnewline
beta & 2.28026532432789 \tabularnewline
S.D. & 1.31670662669902 \tabularnewline
T-STAT & 1.73179452285777 \tabularnewline
p-value & 0.181737219841521 \tabularnewline
Lambda & -1.28026532432789 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62291&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.6612895344685[/C][/ROW]
[ROW][C]beta[/C][C]2.28026532432789[/C][/ROW]
[ROW][C]S.D.[/C][C]1.31670662669902[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.73179452285777[/C][/ROW]
[ROW][C]p-value[/C][C]0.181737219841521[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.28026532432789[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62291&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62291&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-2.6612895344685
beta2.28026532432789
S.D.1.31670662669902
T-STAT1.73179452285777
p-value0.181737219841521
Lambda-1.28026532432789



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')