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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 07 Dec 2007 04:24:16 -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/07/t1197025918gts5h1dibq9421q.htm/, Retrieved Mon, 29 Apr 2024 05:46:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2754, Retrieved Mon, 29 Apr 2024 05:46:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2007-12-07 11:24:16] [e24e91da8d334fb8882bf413603fde71] [Current]
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Dataseries X:
87.0
96.3
107.1
115.2
106.1
89.5
91.3
97.6
100.7
104.6
94.7
101.8
102.5
105.3
110.3
109.8
117.3
118.8
131.3
125.9
133.1
147.0
145.8
164.4
149.8
137.7
151.7
156.8
180.0
180.4
170.4
191.6
199.5
218.2
217.5
205.0
194.0
199.3
219.3
211.1
215.2
240.2
242.2
240.7
255.4
253.0
218.2
203.7
205.6
215.6
188.5
202.9
214.0
230.3
230.0
241.0
259.6
247.8
270.3
289.7




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2754&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]2 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=2754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2754&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.3258.205112042889128.2
2125.95833333333319.077090417248668.1
3179.88333333333327.1994596648648111.1
4224.35833333333321.1482841914521145.6
5232.94166666666730.0209156886974183.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.325 & 8.2051120428891 & 28.2 \tabularnewline
2 & 125.958333333333 & 19.0770904172486 & 68.1 \tabularnewline
3 & 179.883333333333 & 27.1994596648648 & 111.1 \tabularnewline
4 & 224.358333333333 & 21.1482841914521 & 145.6 \tabularnewline
5 & 232.941666666667 & 30.0209156886974 & 183.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2754&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]99.325[/C][C]8.2051120428891[/C][C]28.2[/C][/ROW]
[ROW][C]2[/C][C]125.958333333333[/C][C]19.0770904172486[/C][C]68.1[/C][/ROW]
[ROW][C]3[/C][C]179.883333333333[/C][C]27.1994596648648[/C][C]111.1[/C][/ROW]
[ROW][C]4[/C][C]224.358333333333[/C][C]21.1482841914521[/C][C]145.6[/C][/ROW]
[ROW][C]5[/C][C]232.941666666667[/C][C]30.0209156886974[/C][C]183.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2754&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
199.3258.205112042889128.2
2125.95833333333319.077090417248668.1
3179.88333333333327.1994596648648111.1
4224.35833333333321.1482841914521145.6
5232.94166666666730.0209156886974183.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.996836458245995
beta0.116719501871286
S.D.0.0483351442198105
T-STAT2.41479577138508
p-value0.0946091415339749

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.996836458245995 \tabularnewline
beta & 0.116719501871286 \tabularnewline
S.D. & 0.0483351442198105 \tabularnewline
T-STAT & 2.41479577138508 \tabularnewline
p-value & 0.0946091415339749 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2754&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.996836458245995[/C][/ROW]
[ROW][C]beta[/C][C]0.116719501871286[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0483351442198105[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.41479577138508[/C][/ROW]
[ROW][C]p-value[/C][C]0.0946091415339749[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2754&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2754&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)
alpha0.996836458245995
beta0.116719501871286
S.D.0.0483351442198105
T-STAT2.41479577138508
p-value0.0946091415339749







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.02824828816913
beta1.17498340696938
S.D.0.420496064260016
T-STAT2.79427920220159
p-value0.068175954071766
Lambda-0.174983406969384

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.02824828816913 \tabularnewline
beta & 1.17498340696938 \tabularnewline
S.D. & 0.420496064260016 \tabularnewline
T-STAT & 2.79427920220159 \tabularnewline
p-value & 0.068175954071766 \tabularnewline
Lambda & -0.174983406969384 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2754&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.02824828816913[/C][/ROW]
[ROW][C]beta[/C][C]1.17498340696938[/C][/ROW]
[ROW][C]S.D.[/C][C]0.420496064260016[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.79427920220159[/C][/ROW]
[ROW][C]p-value[/C][C]0.068175954071766[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.174983406969384[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2754&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2754&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-3.02824828816913
beta1.17498340696938
S.D.0.420496064260016
T-STAT2.79427920220159
p-value0.068175954071766
Lambda-0.174983406969384



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')