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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 11 Nov 2008 13:32:28 -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/2008/Nov/11/t1226435613a1lnhbdpcov4tkr.htm/, Retrieved Mon, 20 May 2024 04:56:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23938, Retrieved Mon, 20 May 2024 04:56:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2008-11-11 20:32:28] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23938&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23938&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23938&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 time9 seconds
R Server'George Udny Yule' @ 72.249.76.132







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1102.0833333333337.0530242814803626
2102.4833333333335.7998171340033521.5
3111.1416666666678.575807232964726
4114.60833333333310.372994512266728.1
5113.4758.1144231856838529.8
6118.5916666666679.260027325046429
7119.9333333333336.9655428990702419.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.083333333333 & 7.05302428148036 & 26 \tabularnewline
2 & 102.483333333333 & 5.79981713400335 & 21.5 \tabularnewline
3 & 111.141666666667 & 8.5758072329647 & 26 \tabularnewline
4 & 114.608333333333 & 10.3729945122667 & 28.1 \tabularnewline
5 & 113.475 & 8.11442318568385 & 29.8 \tabularnewline
6 & 118.591666666667 & 9.2600273250464 & 29 \tabularnewline
7 & 119.933333333333 & 6.96554289907024 & 19.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23938&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]102.083333333333[/C][C]7.05302428148036[/C][C]26[/C][/ROW]
[ROW][C]2[/C][C]102.483333333333[/C][C]5.79981713400335[/C][C]21.5[/C][/ROW]
[ROW][C]3[/C][C]111.141666666667[/C][C]8.5758072329647[/C][C]26[/C][/ROW]
[ROW][C]4[/C][C]114.608333333333[/C][C]10.3729945122667[/C][C]28.1[/C][/ROW]
[ROW][C]5[/C][C]113.475[/C][C]8.11442318568385[/C][C]29.8[/C][/ROW]
[ROW][C]6[/C][C]118.591666666667[/C][C]9.2600273250464[/C][C]29[/C][/ROW]
[ROW][C]7[/C][C]119.933333333333[/C][C]6.96554289907024[/C][C]19.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23938&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23938&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
1102.0833333333337.0530242814803626
2102.4833333333335.7998171340033521.5
3111.1416666666678.575807232964726
4114.60833333333310.372994512266728.1
5113.4758.1144231856838529.8
6118.5916666666679.260027325046429
7119.9333333333336.9655428990702419.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5.30787013499757
beta0.119256985682054
S.D.0.0811758885499666
T-STAT1.46911832826624
p-value0.201743201955856

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5.30787013499757 \tabularnewline
beta & 0.119256985682054 \tabularnewline
S.D. & 0.0811758885499666 \tabularnewline
T-STAT & 1.46911832826624 \tabularnewline
p-value & 0.201743201955856 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23938&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.30787013499757[/C][/ROW]
[ROW][C]beta[/C][C]0.119256985682054[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0811758885499666[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.46911832826624[/C][/ROW]
[ROW][C]p-value[/C][C]0.201743201955856[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23938&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23938&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-5.30787013499757
beta0.119256985682054
S.D.0.0811758885499666
T-STAT1.46911832826624
p-value0.201743201955856







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.27477128287619
beta1.76907829520240
S.D.1.10279087492701
T-STAT1.60418292844461
p-value0.169578936035567
Lambda-0.769078295202396

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.27477128287619 \tabularnewline
beta & 1.76907829520240 \tabularnewline
S.D. & 1.10279087492701 \tabularnewline
T-STAT & 1.60418292844461 \tabularnewline
p-value & 0.169578936035567 \tabularnewline
Lambda & -0.769078295202396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23938&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.27477128287619[/C][/ROW]
[ROW][C]beta[/C][C]1.76907829520240[/C][/ROW]
[ROW][C]S.D.[/C][C]1.10279087492701[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.60418292844461[/C][/ROW]
[ROW][C]p-value[/C][C]0.169578936035567[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.769078295202396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23938&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23938&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-6.27477128287619
beta1.76907829520240
S.D.1.10279087492701
T-STAT1.60418292844461
p-value0.169578936035567
Lambda-0.769078295202396



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')