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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, 12 Mar 2015 15:10:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Mar/12/t1426173240qnfss8n49dlw6p8.htm/, Retrieved Fri, 17 May 2024 12:59:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278283, Retrieved Fri, 17 May 2024 12:59:37 +0000
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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)
-       [Standard Deviation-Mean Plot] [] [2015-03-12 15:10:05] [4696c8cdb98c635bcaa184793f2e8dd7] [Current]
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Dataseries X:
2.07
2.2
2.29
2.32
2.37
2.38
2.38
2.28
2.22
2.25
2.3
2.3
2.23
2.27
2.3
2.32
2.41
2.43
2.45
2.47
2.46
2.5
2.46
2.43
2.37
2.45
2.53
2.56
2.62
2.67
2.62
2.6
2.53
2.49
2.48
2.44
2.36
2.35
2.44
2.5
2.58
2.55
2.44
2.3
2.24
2.19
2.25
2.28
2.27
2.37
2.47
2.5
2.47
2.61
2.61
2.65
2.43
2.43
2.33
2.27
2.22
2.17
2.28
2.3
2.33
2.44
2.41
2.4
2.34
2.37
2.38
2.3
2.29
2.34
2.35
2.38
2.37
2.45
2.51
2.46
2.42
2.48
2.44
2.43
2.36
2.42
2.42
2.43
2.47
2.54
2.55
2.55
2.49
2.54
2.55
2.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278283&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278283&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278283&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'Sir Maurice George Kendall' @ kendall.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12.280.08821461433242330.31
22.394166666666670.08959082068780910.27
32.530.08831760866327850.3
42.373333333333330.1280151506185060.39
52.450833333333330.1282368783529020.38
62.328333333333330.0795251056223280.27
72.410.06452624554114670.22
82.4850.06487750695804290.19

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.28 & 0.0882146143324233 & 0.31 \tabularnewline
2 & 2.39416666666667 & 0.0895908206878091 & 0.27 \tabularnewline
3 & 2.53 & 0.0883176086632785 & 0.3 \tabularnewline
4 & 2.37333333333333 & 0.128015150618506 & 0.39 \tabularnewline
5 & 2.45083333333333 & 0.128236878352902 & 0.38 \tabularnewline
6 & 2.32833333333333 & 0.079525105622328 & 0.27 \tabularnewline
7 & 2.41 & 0.0645262455411467 & 0.22 \tabularnewline
8 & 2.485 & 0.0648775069580429 & 0.19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278283&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]2.28[/C][C]0.0882146143324233[/C][C]0.31[/C][/ROW]
[ROW][C]2[/C][C]2.39416666666667[/C][C]0.0895908206878091[/C][C]0.27[/C][/ROW]
[ROW][C]3[/C][C]2.53[/C][C]0.0883176086632785[/C][C]0.3[/C][/ROW]
[ROW][C]4[/C][C]2.37333333333333[/C][C]0.128015150618506[/C][C]0.39[/C][/ROW]
[ROW][C]5[/C][C]2.45083333333333[/C][C]0.128236878352902[/C][C]0.38[/C][/ROW]
[ROW][C]6[/C][C]2.32833333333333[/C][C]0.079525105622328[/C][C]0.27[/C][/ROW]
[ROW][C]7[/C][C]2.41[/C][C]0.0645262455411467[/C][C]0.22[/C][/ROW]
[ROW][C]8[/C][C]2.485[/C][C]0.0648775069580429[/C][C]0.19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278283&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278283&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
12.280.08821461433242330.31
22.394166666666670.08959082068780910.27
32.530.08831760866327850.3
42.373333333333330.1280151506185060.39
52.450833333333330.1282368783529020.38
62.328333333333330.0795251056223280.27
72.410.06452624554114670.22
82.4850.06487750695804290.19







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.131792570718885
beta-0.0167796711094093
S.D.0.123430339653642
T-STAT-0.135944461924797
p-value0.896311593022046

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.131792570718885 \tabularnewline
beta & -0.0167796711094093 \tabularnewline
S.D. & 0.123430339653642 \tabularnewline
T-STAT & -0.135944461924797 \tabularnewline
p-value & 0.896311593022046 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278283&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.131792570718885[/C][/ROW]
[ROW][C]beta[/C][C]-0.0167796711094093[/C][/ROW]
[ROW][C]S.D.[/C][C]0.123430339653642[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.135944461924797[/C][/ROW]
[ROW][C]p-value[/C][C]0.896311593022046[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278283&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278283&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)
alpha0.131792570718885
beta-0.0167796711094093
S.D.0.123430339653642
T-STAT-0.135944461924797
p-value0.896311593022046







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.85562144763672
beta-0.646531706048701
S.D.3.13821660199074
T-STAT-0.206018827903266
p-value0.843588864010383
Lambda1.6465317060487

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.85562144763672 \tabularnewline
beta & -0.646531706048701 \tabularnewline
S.D. & 3.13821660199074 \tabularnewline
T-STAT & -0.206018827903266 \tabularnewline
p-value & 0.843588864010383 \tabularnewline
Lambda & 1.6465317060487 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278283&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.85562144763672[/C][/ROW]
[ROW][C]beta[/C][C]-0.646531706048701[/C][/ROW]
[ROW][C]S.D.[/C][C]3.13821660199074[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.206018827903266[/C][/ROW]
[ROW][C]p-value[/C][C]0.843588864010383[/C][/ROW]
[ROW][C]Lambda[/C][C]1.6465317060487[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278283&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278283&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-1.85562144763672
beta-0.646531706048701
S.D.3.13821660199074
T-STAT-0.206018827903266
p-value0.843588864010383
Lambda1.6465317060487



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')