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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, 14 Dec 2007 03:14:22 -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/14/t11976265101scrmpxz31p90x4.htm/, Retrieved Thu, 02 May 2024 18:33:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3795, Retrieved Thu, 02 May 2024 18:33:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [SMP - Serie 4 - ...] [2007-12-14 10:14:22] [921757a21ec3444367392306fe4aab7f] [Current]
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Dataseries X:
116,2
119,8
117,2
127,3
107,7
97,5
120,1
110,6
111,3
119,8
105,5
108,7
128,7
119,5
121,1
128,4
108,8
107,5
125,6
102,9
107,5
120,4
104,3
100,6
121,9
112,7
124,9
123,9
102,2
104,9
109,8
98,9
107,3
112,6
104
110,6
100,8
103,8
117
108,4
95,5
96,9
103,9
101,1
100,6
104,3
98
99,5
97,4
105,6
117,5
107,4
97,8
91,5
107,7
100,1
96,6
106,8
98
98,6




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=3795&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=3795&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3795&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
1113.4758.1144231856838529.9
2114.60833333333310.372994512266724.9
3111.1416666666678.57580723296477.9
4102.4833333333335.799817134003359.6
5102.0833333333337.0530242814803622

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 113.475 & 8.11442318568385 & 29.9 \tabularnewline
2 & 114.608333333333 & 10.3729945122667 & 24.9 \tabularnewline
3 & 111.141666666667 & 8.5758072329647 & 7.9 \tabularnewline
4 & 102.483333333333 & 5.79981713400335 & 9.6 \tabularnewline
5 & 102.083333333333 & 7.05302428148036 & 22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3795&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]113.475[/C][C]8.11442318568385[/C][C]29.9[/C][/ROW]
[ROW][C]2[/C][C]114.608333333333[/C][C]10.3729945122667[/C][C]24.9[/C][/ROW]
[ROW][C]3[/C][C]111.141666666667[/C][C]8.5758072329647[/C][C]7.9[/C][/ROW]
[ROW][C]4[/C][C]102.483333333333[/C][C]5.79981713400335[/C][C]9.6[/C][/ROW]
[ROW][C]5[/C][C]102.083333333333[/C][C]7.05302428148036[/C][C]22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3795&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3795&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
1113.4758.1144231856838529.9
2114.60833333333310.372994512266724.9
3111.1416666666678.57580723296477.9
4102.4833333333335.799817134003359.6
5102.0833333333337.0530242814803622







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-18.7604265236922
beta0.245899683944268
S.D.0.081050252658127
T-STAT3.03391631586248
p-value0.0561367122155901

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -18.7604265236922 \tabularnewline
beta & 0.245899683944268 \tabularnewline
S.D. & 0.081050252658127 \tabularnewline
T-STAT & 3.03391631586248 \tabularnewline
p-value & 0.0561367122155901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3795&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-18.7604265236922[/C][/ROW]
[ROW][C]beta[/C][C]0.245899683944268[/C][/ROW]
[ROW][C]S.D.[/C][C]0.081050252658127[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.03391631586248[/C][/ROW]
[ROW][C]p-value[/C][C]0.0561367122155901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3795&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3795&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-18.7604265236922
beta0.245899683944268
S.D.0.081050252658127
T-STAT3.03391631586248
p-value0.0561367122155901







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-13.8809018887176
beta3.40015494459472
S.D.1.08734479834948
T-STAT3.12702553022366
p-value0.0521858926863499
Lambda-2.40015494459472

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -13.8809018887176 \tabularnewline
beta & 3.40015494459472 \tabularnewline
S.D. & 1.08734479834948 \tabularnewline
T-STAT & 3.12702553022366 \tabularnewline
p-value & 0.0521858926863499 \tabularnewline
Lambda & -2.40015494459472 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3795&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.8809018887176[/C][/ROW]
[ROW][C]beta[/C][C]3.40015494459472[/C][/ROW]
[ROW][C]S.D.[/C][C]1.08734479834948[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.12702553022366[/C][/ROW]
[ROW][C]p-value[/C][C]0.0521858926863499[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.40015494459472[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3795&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3795&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-13.8809018887176
beta3.40015494459472
S.D.1.08734479834948
T-STAT3.12702553022366
p-value0.0521858926863499
Lambda-2.40015494459472



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')