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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 21 Nov 2014 13:47:27 +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/2014/Nov/21/t14165776689cf5qry0qr24q1e.htm/, Retrieved Tue, 28 May 2024 22:48:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257625, Retrieved Tue, 28 May 2024 22:48:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-11-21 13:47:27] [81bcec4b91879990466572cf43afb80d] [Current]
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Dataseries X:
79.26
79.38
79.35
78.91
79.11
79.22
79.22
79.21
79.26
79.82
80.04
80.2
80.2
80.27
80.37
80.57
79.99
79.86
79.86
79.81
79.88
80.2
80.53
80.52
80.52
80.48
80.29
79.54
79.39
79.3
79.3
79.49
79.63
79.74
80.17
80.06
80.06
80.22
80.5
80.58
80.24
80.34
80.34
80.41
80.59
80.77
80.94
80.8
80.8
80.76
80.94
81.03
81.35
81.41
81.41
81.44
81.55
81.8
81.97
81.99
79.36
79.44
79.46
79.77
79.49
79.42
80.32
80.48
80.6
80.53
80.84
80.68




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257625&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257625&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257625&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 Ronald Aylmer Fisher' @ fisher.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
179.4150.3920227266139291.29000000000001
280.17166666666670.2863828757365760.759999999999991
379.82583333333330.4554410117144881.22
480.48250.2639257815784920.879999999999995
581.37083333333330.4229433302536631.22999999999999
680.03250.5872296283087551.48

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 79.415 & 0.392022726613929 & 1.29000000000001 \tabularnewline
2 & 80.1716666666667 & 0.286382875736576 & 0.759999999999991 \tabularnewline
3 & 79.8258333333333 & 0.455441011714488 & 1.22 \tabularnewline
4 & 80.4825 & 0.263925781578492 & 0.879999999999995 \tabularnewline
5 & 81.3708333333333 & 0.422943330253663 & 1.22999999999999 \tabularnewline
6 & 80.0325 & 0.587229628308755 & 1.48 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257625&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]79.415[/C][C]0.392022726613929[/C][C]1.29000000000001[/C][/ROW]
[ROW][C]2[/C][C]80.1716666666667[/C][C]0.286382875736576[/C][C]0.759999999999991[/C][/ROW]
[ROW][C]3[/C][C]79.8258333333333[/C][C]0.455441011714488[/C][C]1.22[/C][/ROW]
[ROW][C]4[/C][C]80.4825[/C][C]0.263925781578492[/C][C]0.879999999999995[/C][/ROW]
[ROW][C]5[/C][C]81.3708333333333[/C][C]0.422943330253663[/C][C]1.22999999999999[/C][/ROW]
[ROW][C]6[/C][C]80.0325[/C][C]0.587229628308755[/C][C]1.48[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257625&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257625&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
179.4150.3920227266139291.29000000000001
280.17166666666670.2863828757365760.759999999999991
379.82583333333330.4554410117144881.22
480.48250.2639257815784920.879999999999995
581.37083333333330.4229433302536631.22999999999999
680.03250.5872296283087551.48







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.35212046437324
beta-0.0243191729981063
S.D.0.0877500737900568
T-STAT-0.277141339576423
p-value0.795404301509503

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.35212046437324 \tabularnewline
beta & -0.0243191729981063 \tabularnewline
S.D. & 0.0877500737900568 \tabularnewline
T-STAT & -0.277141339576423 \tabularnewline
p-value & 0.795404301509503 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257625&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.35212046437324[/C][/ROW]
[ROW][C]beta[/C][C]-0.0243191729981063[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0877500737900568[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.277141339576423[/C][/ROW]
[ROW][C]p-value[/C][C]0.795404301509503[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257625&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257625&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)
alpha2.35212046437324
beta-0.0243191729981063
S.D.0.0877500737900568
T-STAT-0.277141339576423
p-value0.795404301509503







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha20.7865153264307
beta-4.95729146208127
S.D.17.7885990056828
T-STAT-0.278678015086944
p-value0.794305600990146
Lambda5.95729146208127

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 20.7865153264307 \tabularnewline
beta & -4.95729146208127 \tabularnewline
S.D. & 17.7885990056828 \tabularnewline
T-STAT & -0.278678015086944 \tabularnewline
p-value & 0.794305600990146 \tabularnewline
Lambda & 5.95729146208127 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257625&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]20.7865153264307[/C][/ROW]
[ROW][C]beta[/C][C]-4.95729146208127[/C][/ROW]
[ROW][C]S.D.[/C][C]17.7885990056828[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.278678015086944[/C][/ROW]
[ROW][C]p-value[/C][C]0.794305600990146[/C][/ROW]
[ROW][C]Lambda[/C][C]5.95729146208127[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257625&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257625&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)
alpha20.7865153264307
beta-4.95729146208127
S.D.17.7885990056828
T-STAT-0.278678015086944
p-value0.794305600990146
Lambda5.95729146208127



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')