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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 27 Dec 2012 16:24:21 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/27/t1356643485oel0tsl013dbl8d.htm/, Retrieved Tue, 07 Feb 2023 18:06:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204796, Retrieved Tue, 07 Feb 2023 18:06:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Autocorrelatie In...] [2012-11-12 10:59:56] [41982c7b3984978a38ca838fef047984]
- RMPD  [Bootstrap Plot - Central Tendency] [Bootstrap Plot (m...] [2012-12-27 20:12:14] [41982c7b3984978a38ca838fef047984]
- R P     [Bootstrap Plot - Central Tendency] [Bootstrap Plot (m...] [2012-12-27 20:14:03] [41982c7b3984978a38ca838fef047984]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot (g...] [2012-12-27 20:38:33] [41982c7b3984978a38ca838fef047984]
- R  D        [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot (g...] [2012-12-27 20:42:04] [41982c7b3984978a38ca838fef047984]
- RM              [Standard Deviation-Mean Plot] [Spreidings- en ge...] [2012-12-27 21:24:21] [97ff841fcf87514e420f2e9629cfd808] [Current]
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Dataseries X:
0.75
0.75
0.77
0.78
0.79
1.01
1.16
1.14
1.12
1.1
1.1
1.1
1.1
1.09
1.09
1.1
1.1
1.17
1.15
1.04
0.94
0.88
0.85
0.85
0.85
0.84
0.83
0.8
0.78
1.02
1.19
1.1
0.96
0.87
0.83
0.82
0.81
0.78
0.79
0.8
0.79
0.97
1.01
0.92
0.87
0.84
0.81
0.81
0.83
0.83
0.85
0.88
0.89
1.21
1.32
1.33
1.23
1.16
1.12
1.06
1.08
1.09
1.03
1.04
1.05
1.19
1.14
1.05
0.95
0.87
0.86
0.85




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.9641666666666670.1770186602045280.41
21.030.1173185252363680.32
30.90750.1310881036139090.41
40.850.07675225788801970.23
51.059166666666670.1946305746948830.5
61.016666666666670.1111373706343420.34

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.964166666666667 & 0.177018660204528 & 0.41 \tabularnewline
2 & 1.03 & 0.117318525236368 & 0.32 \tabularnewline
3 & 0.9075 & 0.131088103613909 & 0.41 \tabularnewline
4 & 0.85 & 0.0767522578880197 & 0.23 \tabularnewline
5 & 1.05916666666667 & 0.194630574694883 & 0.5 \tabularnewline
6 & 1.01666666666667 & 0.111137370634342 & 0.34 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&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]0.964166666666667[/C][C]0.177018660204528[/C][C]0.41[/C][/ROW]
[ROW][C]2[/C][C]1.03[/C][C]0.117318525236368[/C][C]0.32[/C][/ROW]
[ROW][C]3[/C][C]0.9075[/C][C]0.131088103613909[/C][C]0.41[/C][/ROW]
[ROW][C]4[/C][C]0.85[/C][C]0.0767522578880197[/C][C]0.23[/C][/ROW]
[ROW][C]5[/C][C]1.05916666666667[/C][C]0.194630574694883[/C][C]0.5[/C][/ROW]
[ROW][C]6[/C][C]1.01666666666667[/C][C]0.111137370634342[/C][C]0.34[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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
10.9641666666666670.1770186602045280.41
21.030.1173185252363680.32
30.90750.1310881036139090.41
40.850.07675225788801970.23
51.059166666666670.1946305746948830.5
61.016666666666670.1111373706343420.34







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.172363484454058
beta0.316109206176988
S.D.0.223526970359861
T-STAT1.41418821034471
p-value0.230206541131741

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.172363484454058 \tabularnewline
beta & 0.316109206176988 \tabularnewline
S.D. & 0.223526970359861 \tabularnewline
T-STAT & 1.41418821034471 \tabularnewline
p-value & 0.230206541131741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.172363484454058[/C][/ROW]
[ROW][C]beta[/C][C]0.316109206176988[/C][/ROW]
[ROW][C]S.D.[/C][C]0.223526970359861[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.41418821034471[/C][/ROW]
[ROW][C]p-value[/C][C]0.230206541131741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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-0.172363484454058
beta0.316109206176988
S.D.0.223526970359861
T-STAT1.41418821034471
p-value0.230206541131741







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.97057982871513
beta2.51209923186973
S.D.1.56378956530374
T-STAT1.60641769686051
p-value0.183457168577422
Lambda-1.51209923186973

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.97057982871513 \tabularnewline
beta & 2.51209923186973 \tabularnewline
S.D. & 1.56378956530374 \tabularnewline
T-STAT & 1.60641769686051 \tabularnewline
p-value & 0.183457168577422 \tabularnewline
Lambda & -1.51209923186973 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.97057982871513[/C][/ROW]
[ROW][C]beta[/C][C]2.51209923186973[/C][/ROW]
[ROW][C]S.D.[/C][C]1.56378956530374[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.60641769686051[/C][/ROW]
[ROW][C]p-value[/C][C]0.183457168577422[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.51209923186973[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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-1.97057982871513
beta2.51209923186973
S.D.1.56378956530374
T-STAT1.60641769686051
p-value0.183457168577422
Lambda-1.51209923186973



Parameters (Session):
par1 = 50 ; par2 = 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')