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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 07:05:38 -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/2013/Dec/05/t1386245274cmim61dsfi8b0vf.htm/, Retrieved Thu, 28 Mar 2024 22:54:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231049, Retrieved Thu, 28 Mar 2024 22:54:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-05 12:05:38] [17e53cb7c94beab0adf1165deaf51c6f] [Current]
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Dataseries X:
3.43
3.43
3.43
3.43
3.43
3.43
3.43
3.43
3.5
3.52
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.58
3.58
3.59
3.59
3.59
3.59
3.59
3.59
3.59
3.59
3.59
3.61
3.71
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.21
4.21
4.21
4.21




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231049&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]3 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=231049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231049&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13.460.04492417854765750.0999999999999996
23.548333333333330.02724746304565340.0600000000000001
33.661666666666670.1070117523990480.24
43.860.04431293675255970.0899999999999999
53.940.02954195783503990.0600000000000001
64.016666666666670.05416025603090630.11
74.130.05908391567007980.12

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3.46 & 0.0449241785476575 & 0.0999999999999996 \tabularnewline
2 & 3.54833333333333 & 0.0272474630456534 & 0.0600000000000001 \tabularnewline
3 & 3.66166666666667 & 0.107011752399048 & 0.24 \tabularnewline
4 & 3.86 & 0.0443129367525597 & 0.0899999999999999 \tabularnewline
5 & 3.94 & 0.0295419578350399 & 0.0600000000000001 \tabularnewline
6 & 4.01666666666667 & 0.0541602560309063 & 0.11 \tabularnewline
7 & 4.13 & 0.0590839156700798 & 0.12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231049&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]3.46[/C][C]0.0449241785476575[/C][C]0.0999999999999996[/C][/ROW]
[ROW][C]2[/C][C]3.54833333333333[/C][C]0.0272474630456534[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]3[/C][C]3.66166666666667[/C][C]0.107011752399048[/C][C]0.24[/C][/ROW]
[ROW][C]4[/C][C]3.86[/C][C]0.0443129367525597[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]5[/C][C]3.94[/C][C]0.0295419578350399[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]6[/C][C]4.01666666666667[/C][C]0.0541602560309063[/C][C]0.11[/C][/ROW]
[ROW][C]7[/C][C]4.13[/C][C]0.0590839156700798[/C][C]0.12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231049&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
13.460.04492417854765750.0999999999999996
23.548333333333330.02724746304565340.0600000000000001
33.661666666666670.1070117523990480.24
43.860.04431293675255970.0899999999999999
53.940.02954195783503990.0600000000000001
64.016666666666670.05416025603090630.11
74.130.05908391567007980.12







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0501058863219433
beta0.00058389189833468
S.D.0.0477926523042783
T-STAT0.012217189676297
p-value0.990724823016512

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0501058863219433 \tabularnewline
beta & 0.00058389189833468 \tabularnewline
S.D. & 0.0477926523042783 \tabularnewline
T-STAT & 0.012217189676297 \tabularnewline
p-value & 0.990724823016512 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231049&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0501058863219433[/C][/ROW]
[ROW][C]beta[/C][C]0.00058389189833468[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0477926523042783[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.012217189676297[/C][/ROW]
[ROW][C]p-value[/C][C]0.990724823016512[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231049&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231049&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)
alpha0.0501058863219433
beta0.00058389189833468
S.D.0.0477926523042783
T-STAT0.012217189676297
p-value0.990724823016512







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.07526070905726
beta0.771553158140498
S.D.3.07815720447587
T-STAT0.250654241121474
p-value0.812055638981001
Lambda0.228446841859502

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.07526070905726 \tabularnewline
beta & 0.771553158140498 \tabularnewline
S.D. & 3.07815720447587 \tabularnewline
T-STAT & 0.250654241121474 \tabularnewline
p-value & 0.812055638981001 \tabularnewline
Lambda & 0.228446841859502 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231049&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.07526070905726[/C][/ROW]
[ROW][C]beta[/C][C]0.771553158140498[/C][/ROW]
[ROW][C]S.D.[/C][C]3.07815720447587[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.250654241121474[/C][/ROW]
[ROW][C]p-value[/C][C]0.812055638981001[/C][/ROW]
[ROW][C]Lambda[/C][C]0.228446841859502[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231049&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231049&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-4.07526070905726
beta0.771553158140498
S.D.3.07815720447587
T-STAT0.250654241121474
p-value0.812055638981001
Lambda0.228446841859502



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')