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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 29 Apr 2013 04:47:56 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Apr/29/t1367225342web9tlr9p0aa8vz.htm/, Retrieved Fri, 03 May 2024 04:23:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208485, Retrieved Fri, 03 May 2024 04:23:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [standaarddeviatie...] [2013-04-29 08:47:56] [2ad6cfb061f4abd47c32d0a7b72d8383] [Current]
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Dataseries X:
4.69
4.69
4.69
4.69
4.69
4.69
4.69
4.73
4.78
4.79
4.79
4.8
4.8
4.81
5.16
5.26
5.29
5.29
5.29
5.3
5.3
5.3
5.3
5.3
5.3
5.3
5.3
5.35
5.44
5.47
5.47
5.48
5.48
5.48
5.48
5.48
5.48
5.48
5.5
5.55
5.57
5.58
5.58
5.58
5.59
5.59
5.59
5.55
5.61
5.61
5.61
5.63
5.69
5.7
5.7
5.7
5.7
5.7
5.7
5.7
5.7
5.7
5.7
5.71
5.74
5.77
5.79
5.79
5.8
5.8
5.8
5.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208485&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208485&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208485&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.726666666666670.04830458915396460.109999999999999
25.20.1886796226411320.5
35.419166666666670.08061787906068020.180000000000001
45.553333333333330.04271115105265150.109999999999999
55.670833333333330.04166060561977060.0899999999999999
65.758333333333330.0446874668891590.0999999999999996

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.72666666666667 & 0.0483045891539646 & 0.109999999999999 \tabularnewline
2 & 5.2 & 0.188679622641132 & 0.5 \tabularnewline
3 & 5.41916666666667 & 0.0806178790606802 & 0.180000000000001 \tabularnewline
4 & 5.55333333333333 & 0.0427111510526515 & 0.109999999999999 \tabularnewline
5 & 5.67083333333333 & 0.0416606056197706 & 0.0899999999999999 \tabularnewline
6 & 5.75833333333333 & 0.044687466889159 & 0.0999999999999996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208485&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]4.72666666666667[/C][C]0.0483045891539646[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]2[/C][C]5.2[/C][C]0.188679622641132[/C][C]0.5[/C][/ROW]
[ROW][C]3[/C][C]5.41916666666667[/C][C]0.0806178790606802[/C][C]0.180000000000001[/C][/ROW]
[ROW][C]4[/C][C]5.55333333333333[/C][C]0.0427111510526515[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]5[/C][C]5.67083333333333[/C][C]0.0416606056197706[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]6[/C][C]5.75833333333333[/C][C]0.044687466889159[/C][C]0.0999999999999996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208485&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208485&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
14.726666666666670.04830458915396460.109999999999999
25.20.1886796226411320.5
35.419166666666670.08061787906068020.180000000000001
45.553333333333330.04271115105265150.109999999999999
55.670833333333330.04166060561977060.0899999999999999
65.758333333333330.0446874668891590.0999999999999996







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.296038691666199
beta-0.0411271073541219
S.D.0.0735119401682599
T-STAT-0.55946159576236
p-value0.605690622337855

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.296038691666199 \tabularnewline
beta & -0.0411271073541219 \tabularnewline
S.D. & 0.0735119401682599 \tabularnewline
T-STAT & -0.55946159576236 \tabularnewline
p-value & 0.605690622337855 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208485&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.296038691666199[/C][/ROW]
[ROW][C]beta[/C][C]-0.0411271073541219[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0735119401682599[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.55946159576236[/C][/ROW]
[ROW][C]p-value[/C][C]0.605690622337855[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208485&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208485&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)
alpha0.296038691666199
beta-0.0411271073541219
S.D.0.0735119401682599
T-STAT-0.55946159576236
p-value0.605690622337855







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.964729505265585
beta-2.22388523198388
S.D.3.94758118894009
T-STAT-0.563353893319414
p-value0.603275605473816
Lambda3.22388523198388

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.964729505265585 \tabularnewline
beta & -2.22388523198388 \tabularnewline
S.D. & 3.94758118894009 \tabularnewline
T-STAT & -0.563353893319414 \tabularnewline
p-value & 0.603275605473816 \tabularnewline
Lambda & 3.22388523198388 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208485&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.964729505265585[/C][/ROW]
[ROW][C]beta[/C][C]-2.22388523198388[/C][/ROW]
[ROW][C]S.D.[/C][C]3.94758118894009[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.563353893319414[/C][/ROW]
[ROW][C]p-value[/C][C]0.603275605473816[/C][/ROW]
[ROW][C]Lambda[/C][C]3.22388523198388[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208485&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208485&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)
alpha0.964729505265585
beta-2.22388523198388
S.D.3.94758118894009
T-STAT-0.563353893319414
p-value0.603275605473816
Lambda3.22388523198388



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')