Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 15 Aug 2008 06:28:52 -0600
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/Aug/15/t12188034916tqi22ssknj8kja.htm/, Retrieved Thu, 16 May 2024 03:28:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14573, Retrieved Thu, 16 May 2024 03:28:43 +0000
QR Codes:

Original text written by user:Spreidings- en gemiddeldegrafieken, goede cijferreeks!
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact252
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Opgave 8 oef 2 - ...] [2008-08-15 12:28:52] [f38aed22bcf737d6f431a6f90e40d4b2] [Current]
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Dataseries X:
0.91
0.9
0.89
0.89
0.89
0.89
0.89
0.89
0.88
0.88
0.88
0.86
0.85
0.85
0.86
0.9
0.92
0.91
0.93
0.96
0.96
0.97
0.98
1.01
0.99
1.03
1.08
1.06
1.1
1.17
1.16
1.12
1.17
1.13
1.12
1.07
1.04
1.08
1.06
1.12
1.18
1.13
1.08
1.06
1.09
1.02
1.01
1.01
1
1.01
1.03
1.09
1.07
1.05
1.06
1.06
1.08
1.07
1.04
1.04
1.06
1.09
1.09
1.05
1.01
1.02
1.03
1.06
1.08
1.05
1.05
1.05
1.04
1.05
1.07
1.1
1.16
1.16
1.17
1.17
1.18
1.21
1.18
1.13
1.12
1.17
1.19
1.26
1.25
1.28
1.35
1.39
1.45
1.41
1.32
1.31




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14573&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14573&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.88750.01215431087011000.05
20.9250.05317210478505370.16
31.10.05640760748177660.18
41.073333333333330.05175700801618920.17
51.050.02730301348669310.09
61.053333333333330.02534608929251700.08
71.1350.05648813230147630.17
81.291666666666670.1003478797468930.33

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.8875 & 0.0121543108701100 & 0.05 \tabularnewline
2 & 0.925 & 0.0531721047850537 & 0.16 \tabularnewline
3 & 1.1 & 0.0564076074817766 & 0.18 \tabularnewline
4 & 1.07333333333333 & 0.0517570080161892 & 0.17 \tabularnewline
5 & 1.05 & 0.0273030134866931 & 0.09 \tabularnewline
6 & 1.05333333333333 & 0.0253460892925170 & 0.08 \tabularnewline
7 & 1.135 & 0.0564881323014763 & 0.17 \tabularnewline
8 & 1.29166666666667 & 0.100347879746893 & 0.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14573&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]0.8875[/C][C]0.0121543108701100[/C][C]0.05[/C][/ROW]
[ROW][C]2[/C][C]0.925[/C][C]0.0531721047850537[/C][C]0.16[/C][/ROW]
[ROW][C]3[/C][C]1.1[/C][C]0.0564076074817766[/C][C]0.18[/C][/ROW]
[ROW][C]4[/C][C]1.07333333333333[/C][C]0.0517570080161892[/C][C]0.17[/C][/ROW]
[ROW][C]5[/C][C]1.05[/C][C]0.0273030134866931[/C][C]0.09[/C][/ROW]
[ROW][C]6[/C][C]1.05333333333333[/C][C]0.0253460892925170[/C][C]0.08[/C][/ROW]
[ROW][C]7[/C][C]1.135[/C][C]0.0564881323014763[/C][C]0.17[/C][/ROW]
[ROW][C]8[/C][C]1.29166666666667[/C][C]0.100347879746893[/C][C]0.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14573&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
10.88750.01215431087011000.05
20.9250.05317210478505370.16
31.10.05640760748177660.18
41.073333333333330.05175700801618920.17
51.050.02730301348669310.09
61.053333333333330.02534608929251700.08
71.1350.05648813230147630.17
81.291666666666670.1003478797468930.33







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.137596161743465
beta0.174233734016451
S.D.0.0530351960328263
T-STAT3.28524728952843
p-value0.0167126749775281

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.137596161743465 \tabularnewline
beta & 0.174233734016451 \tabularnewline
S.D. & 0.0530351960328263 \tabularnewline
T-STAT & 3.28524728952843 \tabularnewline
p-value & 0.0167126749775281 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14573&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.137596161743465[/C][/ROW]
[ROW][C]beta[/C][C]0.174233734016451[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0530351960328263[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.28524728952843[/C][/ROW]
[ROW][C]p-value[/C][C]0.0167126749775281[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14573&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14573&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-0.137596161743465
beta0.174233734016451
S.D.0.0530351960328263
T-STAT3.28524728952843
p-value0.0167126749775281







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.44091487592901
beta4.19820527030479
S.D.1.51725744107827
T-STAT2.76696963655769
p-value0.0325526033303637
Lambda-3.19820527030479

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.44091487592901 \tabularnewline
beta & 4.19820527030479 \tabularnewline
S.D. & 1.51725744107827 \tabularnewline
T-STAT & 2.76696963655769 \tabularnewline
p-value & 0.0325526033303637 \tabularnewline
Lambda & -3.19820527030479 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14573&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.44091487592901[/C][/ROW]
[ROW][C]beta[/C][C]4.19820527030479[/C][/ROW]
[ROW][C]S.D.[/C][C]1.51725744107827[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.76696963655769[/C][/ROW]
[ROW][C]p-value[/C][C]0.0325526033303637[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.19820527030479[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14573&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14573&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-3.44091487592901
beta4.19820527030479
S.D.1.51725744107827
T-STAT2.76696963655769
p-value0.0325526033303637
Lambda-3.19820527030479



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
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')