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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 03 Dec 2013 08:15:21 -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/2013/Dec/03/t1386076616hfaasnyct69mn9h.htm/, Retrieved Fri, 19 Apr 2024 03:23:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230285, Retrieved Fri, 19 Apr 2024 03:23:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact53
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-03 13:15:21] [a9b531f12fa224c0c22271b290223f8e] [Current]
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Dataseries X:
1.27
1.26
1.26
1.27
1.27
1.28
1.28
1.28
1.29
1.29
1.29
1.29
1.3
1.31
1.31
1.32
1.32
1.32
1.32
1.32
1.32
1.33
1.32
1.33
1.34
1.35
1.35
1.35
1.35
1.35
1.35
1.35
1.36
1.35
1.36
1.36
1.37
1.38
1.38
1.38
1.39
1.39
1.39
1.39
1.39
1.4
1.39
1.39
1.4
1.4
1.4
1.41
1.41
1.42
1.42
1.43
1.43
1.44
1.43
1.43
1.43
1.44
1.44
1.44
1.43
1.44
1.45
1.45
1.48
1.49
1.49
1.51
1.52
1.53
1.53
1.54
1.54
1.54
1.57
1.59
1.58
1.6
1.62
1.62




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230285&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230285&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230285&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'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.27750.01138180365958990.03
21.318333333333330.008348471099367230.03
31.351666666666670.005773502691896260.02
41.386666666666670.007784989441615190.0299999999999998
51.418333333333330.01403458930534480.04
61.45750.02734460225944550.0800000000000001
71.5650.03630677372311980.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.2775 & 0.0113818036595899 & 0.03 \tabularnewline
2 & 1.31833333333333 & 0.00834847109936723 & 0.03 \tabularnewline
3 & 1.35166666666667 & 0.00577350269189626 & 0.02 \tabularnewline
4 & 1.38666666666667 & 0.00778498944161519 & 0.0299999999999998 \tabularnewline
5 & 1.41833333333333 & 0.0140345893053448 & 0.04 \tabularnewline
6 & 1.4575 & 0.0273446022594455 & 0.0800000000000001 \tabularnewline
7 & 1.565 & 0.0363067737231198 & 0.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230285&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]1.2775[/C][C]0.0113818036595899[/C][C]0.03[/C][/ROW]
[ROW][C]2[/C][C]1.31833333333333[/C][C]0.00834847109936723[/C][C]0.03[/C][/ROW]
[ROW][C]3[/C][C]1.35166666666667[/C][C]0.00577350269189626[/C][C]0.02[/C][/ROW]
[ROW][C]4[/C][C]1.38666666666667[/C][C]0.00778498944161519[/C][C]0.0299999999999998[/C][/ROW]
[ROW][C]5[/C][C]1.41833333333333[/C][C]0.0140345893053448[/C][C]0.04[/C][/ROW]
[ROW][C]6[/C][C]1.4575[/C][C]0.0273446022594455[/C][C]0.0800000000000001[/C][/ROW]
[ROW][C]7[/C][C]1.565[/C][C]0.0363067737231198[/C][C]0.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230285&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230285&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
11.27750.01138180365958990.03
21.318333333333330.008348471099367230.03
31.351666666666670.005773502691896260.02
41.386666666666670.007784989441615190.0299999999999998
51.418333333333330.01403458930534480.04
61.45750.02734460225944550.0800000000000001
71.5650.03630677372311980.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.130417124606613
beta0.104746251092243
S.D.0.0265425923165375
T-STAT3.94634592744657
p-value0.0108904815068424

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.130417124606613 \tabularnewline
beta & 0.104746251092243 \tabularnewline
S.D. & 0.0265425923165375 \tabularnewline
T-STAT & 3.94634592744657 \tabularnewline
p-value & 0.0108904815068424 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230285&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.130417124606613[/C][/ROW]
[ROW][C]beta[/C][C]0.104746251092243[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0265425923165375[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.94634592744657[/C][/ROW]
[ROW][C]p-value[/C][C]0.0108904815068424[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230285&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230285&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-0.130417124606613
beta0.104746251092243
S.D.0.0265425923165375
T-STAT3.94634592744657
p-value0.0108904815068424







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.984996470662
beta7.93693580112968
S.D.2.73460699753966
T-STAT2.90240455329434
p-value0.033696223230097
Lambda-6.93693580112968

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.984996470662 \tabularnewline
beta & 7.93693580112968 \tabularnewline
S.D. & 2.73460699753966 \tabularnewline
T-STAT & 2.90240455329434 \tabularnewline
p-value & 0.033696223230097 \tabularnewline
Lambda & -6.93693580112968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230285&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.984996470662[/C][/ROW]
[ROW][C]beta[/C][C]7.93693580112968[/C][/ROW]
[ROW][C]S.D.[/C][C]2.73460699753966[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.90240455329434[/C][/ROW]
[ROW][C]p-value[/C][C]0.033696223230097[/C][/ROW]
[ROW][C]Lambda[/C][C]-6.93693580112968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230285&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230285&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-6.984996470662
beta7.93693580112968
S.D.2.73460699753966
T-STAT2.90240455329434
p-value0.033696223230097
Lambda-6.93693580112968



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')