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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 19 Dec 2007 08:18:17 -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/Dec/19/t119807704221pwt42dcu0gueg.htm/, Retrieved Mon, 06 May 2024 21:26:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4671, Retrieved Mon, 06 May 2024 21:26:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact218
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [SMP inves] [2007-12-19 15:18:17] [7c5f7a910a5108d789a748f71ee8daf4] [Current]
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Dataseries X:
93.9
89.8
93.4
101.5
110.4
105.9
108.4
113.9
86.1
69.4
101.2
100.5
98.0
106.6
90.1
96.9
125.9
112.0
100.0
123.9
79.8
83.4
113.6
112.9
104.0
109.9
99.0
106.3
128.9
111.1
102.9
130.0
87.0
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137.0
91.0
90.5
122.4
123.3
124.3
120.0
118.1
119.0
142.7
123.6
129.6
151.6
110.4
99.3
129.1
134.1




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=4671&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=4671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4671&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
197.866666666666712.323099767460620
2103.59166666666714.836592253511936.1
3107.313.580132547217639.9
4114.24166666666715.512661006905040.1
5125.1513.902485062358141.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 97.8666666666667 & 12.3230997674606 & 20 \tabularnewline
2 & 103.591666666667 & 14.8365922535119 & 36.1 \tabularnewline
3 & 107.3 & 13.5801325472176 & 39.9 \tabularnewline
4 & 114.241666666667 & 15.5126610069050 & 40.1 \tabularnewline
5 & 125.15 & 13.9024850623581 & 41.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4671&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]97.8666666666667[/C][C]12.3230997674606[/C][C]20[/C][/ROW]
[ROW][C]2[/C][C]103.591666666667[/C][C]14.8365922535119[/C][C]36.1[/C][/ROW]
[ROW][C]3[/C][C]107.3[/C][C]13.5801325472176[/C][C]39.9[/C][/ROW]
[ROW][C]4[/C][C]114.241666666667[/C][C]15.5126610069050[/C][C]40.1[/C][/ROW]
[ROW][C]5[/C][C]125.15[/C][C]13.9024850623581[/C][C]41.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4671&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
197.866666666666712.323099767460620
2103.59166666666714.836592253511936.1
3107.313.580132547217639.9
4114.24166666666715.512661006905040.1
5125.1513.902485062358141.2







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.79857568214946
beta0.0477279799812205
S.D.0.0612138120454406
T-STAT0.779692987357016
p-value0.492429433652316

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.79857568214946 \tabularnewline
beta & 0.0477279799812205 \tabularnewline
S.D. & 0.0612138120454406 \tabularnewline
T-STAT & 0.779692987357016 \tabularnewline
p-value & 0.492429433652316 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4671&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.79857568214946[/C][/ROW]
[ROW][C]beta[/C][C]0.0477279799812205[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0612138120454406[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.779692987357016[/C][/ROW]
[ROW][C]p-value[/C][C]0.492429433652316[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4671&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4671&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)
alpha8.79857568214946
beta0.0477279799812205
S.D.0.0612138120454406
T-STAT0.779692987357016
p-value0.492429433652316







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.649555395906203
beta0.42369738565282
S.D.0.480431232903171
T-STAT0.881910576655233
p-value0.442766164456268
Lambda0.57630261434718

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.649555395906203 \tabularnewline
beta & 0.42369738565282 \tabularnewline
S.D. & 0.480431232903171 \tabularnewline
T-STAT & 0.881910576655233 \tabularnewline
p-value & 0.442766164456268 \tabularnewline
Lambda & 0.57630261434718 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4671&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.649555395906203[/C][/ROW]
[ROW][C]beta[/C][C]0.42369738565282[/C][/ROW]
[ROW][C]S.D.[/C][C]0.480431232903171[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.881910576655233[/C][/ROW]
[ROW][C]p-value[/C][C]0.442766164456268[/C][/ROW]
[ROW][C]Lambda[/C][C]0.57630261434718[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4671&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4671&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)
alpha0.649555395906203
beta0.42369738565282
S.D.0.480431232903171
T-STAT0.881910576655233
p-value0.442766164456268
Lambda0.57630261434718



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')