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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, 12 Mar 2015 16:12:00 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Mar/12/t1426176740s5v4knbjjtlqq51.htm/, Retrieved Fri, 17 May 2024 13:27:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278311, Retrieved Fri, 17 May 2024 13:27:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [spreidings- en ge...] [2015-03-12 16:12:00] [b807b9265c4c1efe31f917466850b643] [Current]
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Dataseries X:
100,05
100,05
100,05
100,05
100,05
108,77
111,32
111,6
108,52
103,13
102,87
102,75
102,75
102,75
102,75
102,75
102,75
115,22
115,53
115,4
111,99
107,93
107,43
106,98
106,98
106,98
106,98
106,98
106,98
113,71
118,77
118,54
116,16
110,52
110,06
109,9
109,9
110,72
110,09
110,07
112,45
113,06
119,83
119,84
113,73
110,5
110,12
109,86
110,36
110,36
110,59
112,52
112,1
115,9
122,96
121,26
114,55
111,57
110,65
109,77
112,38
112,35
112,2
114,46
116,26
119,57
127,77
126,59
120,45
116,38
116,3
115,05
115,05
115,22
115,19
116,07
120,42
121,88
130,74
130,74
124,64
120,5
120,1
119,62




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278311&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278311&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278311&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1104.1008333333334.6320277482551911.55
2107.85255.3803601180590112.78
3111.0466666666674.6151338665374111.79
4112.5141666666673.664404846463879.98
5113.5491666666674.4046534449031313.19
6117.485.2343845691907115.57
7120.84755.5074563094045615.69

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 104.100833333333 & 4.63202774825519 & 11.55 \tabularnewline
2 & 107.8525 & 5.38036011805901 & 12.78 \tabularnewline
3 & 111.046666666667 & 4.61513386653741 & 11.79 \tabularnewline
4 & 112.514166666667 & 3.66440484646387 & 9.98 \tabularnewline
5 & 113.549166666667 & 4.40465344490313 & 13.19 \tabularnewline
6 & 117.48 & 5.23438456919071 & 15.57 \tabularnewline
7 & 120.8475 & 5.50745630940456 & 15.69 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278311&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]104.100833333333[/C][C]4.63202774825519[/C][C]11.55[/C][/ROW]
[ROW][C]2[/C][C]107.8525[/C][C]5.38036011805901[/C][C]12.78[/C][/ROW]
[ROW][C]3[/C][C]111.046666666667[/C][C]4.61513386653741[/C][C]11.79[/C][/ROW]
[ROW][C]4[/C][C]112.514166666667[/C][C]3.66440484646387[/C][C]9.98[/C][/ROW]
[ROW][C]5[/C][C]113.549166666667[/C][C]4.40465344490313[/C][C]13.19[/C][/ROW]
[ROW][C]6[/C][C]117.48[/C][C]5.23438456919071[/C][C]15.57[/C][/ROW]
[ROW][C]7[/C][C]120.8475[/C][C]5.50745630940456[/C][C]15.69[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278311&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278311&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
1104.1008333333334.6320277482551911.55
2107.85255.3803601180590112.78
3111.0466666666674.6151338665374111.79
4112.5141666666673.664404846463879.98
5113.5491666666674.4046534449031313.19
6117.485.2343845691907115.57
7120.84755.5074563094045615.69







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.855792031776579
beta0.0348592789227431
S.D.0.0492236293474953
T-STAT0.708181809932243
p-value0.510471129455718

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.855792031776579 \tabularnewline
beta & 0.0348592789227431 \tabularnewline
S.D. & 0.0492236293474953 \tabularnewline
T-STAT & 0.708181809932243 \tabularnewline
p-value & 0.510471129455718 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278311&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.855792031776579[/C][/ROW]
[ROW][C]beta[/C][C]0.0348592789227431[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0492236293474953[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.708181809932243[/C][/ROW]
[ROW][C]p-value[/C][C]0.510471129455718[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278311&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278311&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)
alpha0.855792031776579
beta0.0348592789227431
S.D.0.0492236293474953
T-STAT0.708181809932243
p-value0.510471129455718







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.93093687621232
beta0.738357441157121
S.D.1.22608011297512
T-STAT0.602209784942579
p-value0.573299447844947
Lambda0.261642558842879

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.93093687621232 \tabularnewline
beta & 0.738357441157121 \tabularnewline
S.D. & 1.22608011297512 \tabularnewline
T-STAT & 0.602209784942579 \tabularnewline
p-value & 0.573299447844947 \tabularnewline
Lambda & 0.261642558842879 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278311&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.93093687621232[/C][/ROW]
[ROW][C]beta[/C][C]0.738357441157121[/C][/ROW]
[ROW][C]S.D.[/C][C]1.22608011297512[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.602209784942579[/C][/ROW]
[ROW][C]p-value[/C][C]0.573299447844947[/C][/ROW]
[ROW][C]Lambda[/C][C]0.261642558842879[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278311&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278311&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-1.93093687621232
beta0.738357441157121
S.D.1.22608011297512
T-STAT0.602209784942579
p-value0.573299447844947
Lambda0.261642558842879



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')