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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, 22 Nov 2007 07:20:36 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/22/t1195740763mu7b0e793il1kfg.htm/, Retrieved Thu, 02 May 2024 23:42:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6015, Retrieved Thu, 02 May 2024 23:42:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [WS7 Q1 G6 reeks 3] [2007-11-22 14:20:36] [fef19078983b9fa83d10cb717d6f9786] [Current]
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Dataseries X:
88,8
93,4
92,6
90,7
81,6
84,1
88,1
85,3
82,9
84,8
71,2
68,9
94,3
97,6
85,6
91,9
75,8
79,8
99
88,5
86,7
97,9
94,3
72,9
91,8
93,2
86,5
98,9
77,2
79,4
90,4
81,4
85,8
103,6
73,6
75,7
99,2
88,7
94,6
98,7
84,2
87,7
103,3
88,2
93,4
106,3
73,1
78,6
101,6
101,4
98,5
99
89,5
83,5
97,4
87,8
90,4
97,1
79,4
85




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6015&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6015&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6015&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
184.36666666666677.666969690981194.60000000000001
288.69166666666678.799840735473410.3
386.45833333333339.4425977101193718
491.33333333333339.879854004564815.6
592.557.566493123093325.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 84.3666666666667 & 7.66696969098119 & 4.60000000000001 \tabularnewline
2 & 88.6916666666667 & 8.7998407354734 & 10.3 \tabularnewline
3 & 86.4583333333333 & 9.44259771011937 & 18 \tabularnewline
4 & 91.3333333333333 & 9.8798540045648 & 15.6 \tabularnewline
5 & 92.55 & 7.5664931230933 & 25.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6015&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]84.3666666666667[/C][C]7.66696969098119[/C][C]4.60000000000001[/C][/ROW]
[ROW][C]2[/C][C]88.6916666666667[/C][C]8.7998407354734[/C][C]10.3[/C][/ROW]
[ROW][C]3[/C][C]86.4583333333333[/C][C]9.44259771011937[/C][C]18[/C][/ROW]
[ROW][C]4[/C][C]91.3333333333333[/C][C]9.8798540045648[/C][C]15.6[/C][/ROW]
[ROW][C]5[/C][C]92.55[/C][C]7.5664931230933[/C][C]25.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6015&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6015&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
184.36666666666677.666969690981194.60000000000001
288.69166666666678.799840735473410.3
386.45833333333339.4425977101193718
491.33333333333339.879854004564815.6
592.557.566493123093325.8







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.65199907120862
beta0.0340454666400293
S.D.0.176309366034699
T-STAT0.1931007263297
p-value0.859213869768713

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.65199907120862 \tabularnewline
beta & 0.0340454666400293 \tabularnewline
S.D. & 0.176309366034699 \tabularnewline
T-STAT & 0.1931007263297 \tabularnewline
p-value & 0.859213869768713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6015&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.65199907120862[/C][/ROW]
[ROW][C]beta[/C][C]0.0340454666400293[/C][/ROW]
[ROW][C]S.D.[/C][C]0.176309366034699[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.1931007263297[/C][/ROW]
[ROW][C]p-value[/C][C]0.859213869768713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6015&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6015&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)
alpha5.65199907120862
beta0.0340454666400293
S.D.0.176309366034699
T-STAT0.1931007263297
p-value0.859213869768713







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.62436523461502
beta0.341146944617128
S.D.1.81259939925348
T-STAT0.188208682380469
p-value0.86272444579678
Lambda0.658853055382872

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.62436523461502 \tabularnewline
beta & 0.341146944617128 \tabularnewline
S.D. & 1.81259939925348 \tabularnewline
T-STAT & 0.188208682380469 \tabularnewline
p-value & 0.86272444579678 \tabularnewline
Lambda & 0.658853055382872 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6015&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.62436523461502[/C][/ROW]
[ROW][C]beta[/C][C]0.341146944617128[/C][/ROW]
[ROW][C]S.D.[/C][C]1.81259939925348[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.188208682380469[/C][/ROW]
[ROW][C]p-value[/C][C]0.86272444579678[/C][/ROW]
[ROW][C]Lambda[/C][C]0.658853055382872[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6015&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6015&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)
alpha0.62436523461502
beta0.341146944617128
S.D.1.81259939925348
T-STAT0.188208682380469
p-value0.86272444579678
Lambda0.658853055382872



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')