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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 04 Jun 2009 09:02:03 -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/2009/Jun/04/t12441277676qhfwxd2powgy1j.htm/, Retrieved Mon, 13 May 2024 21:33:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41703, Retrieved Mon, 13 May 2024 21:33:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Quartiles] [k
- RMPD    [Standard Deviation-Mean Plot] [] [2009-06-04 15:02:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.73
1.75
1.75
1.75
1.73
1.74
1.75
1.75
1.34
1.24
1.24
1.26
1.25
1.26
1.26
1.22
1.01
1.03
1.01
1.01
1
0.98
1
1.01
1
1
1
1.03
1.26
1.43
1.61
1.76
1.93
2.16
2.28
2.5
2.63
2.79
3
3.04
3.26
3.5
3.62
3.78
4
4.16
4.29
4.49
4.59
4.79
4.94
4.99
5.24
5.25
5.25
5.25
5.25
5.24
5.25
5.26
5.26
5.25
5.25
5.25
5.26
5.02
4.94
4.76
4.49
4.24
3.94
2.98
2.61
2.28
1.98
2
2.01
2
1.81
0.97
0.39
0.16
0.15
0.22

Tables (Output of Computation)





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=41703&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=41703&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41703&T=0

As an alternative you can also use a QR Code:  
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
11.585833333333330.2346935461534050.51
21.086666666666670.1197218999737860.28
31.580.5448269116300731.5
43.546666666666670.6132378054724011.86
55.108333333333330.2277092777018870.67
64.720.7061547602718162.28
71.381666666666670.9307165698177582.46

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.58583333333333 & 0.234693546153405 & 0.51 \tabularnewline
2 & 1.08666666666667 & 0.119721899973786 & 0.28 \tabularnewline
3 & 1.58 & 0.544826911630073 & 1.5 \tabularnewline
4 & 3.54666666666667 & 0.613237805472401 & 1.86 \tabularnewline
5 & 5.10833333333333 & 0.227709277701887 & 0.67 \tabularnewline
6 & 4.72 & 0.706154760271816 & 2.28 \tabularnewline
7 & 1.38166666666667 & 0.930716569817758 & 2.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41703&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]1.58583333333333[/C][C]0.234693546153405[/C][C]0.51[/C][/ROW]
[ROW][C]2[/C][C]1.08666666666667[/C][C]0.119721899973786[/C][C]0.28[/C][/ROW]
[ROW][C]3[/C][C]1.58[/C][C]0.544826911630073[/C][C]1.5[/C][/ROW]
[ROW][C]4[/C][C]3.54666666666667[/C][C]0.613237805472401[/C][C]1.86[/C][/ROW]
[ROW][C]5[/C][C]5.10833333333333[/C][C]0.227709277701887[/C][C]0.67[/C][/ROW]
[ROW][C]6[/C][C]4.72[/C][C]0.706154760271816[/C][C]2.28[/C][/ROW]
[ROW][C]7[/C][C]1.38166666666667[/C][C]0.930716569817758[/C][C]2.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41703&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41703&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.585833333333330.2346935461534050.51
21.086666666666670.1197218999737860.28
31.580.5448269116300731.5
43.546666666666670.6132378054724011.86
55.108333333333330.2277092777018870.67
64.720.7061547602718162.28
71.381666666666670.9307165698177582.46






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.459142738411067
beta0.00857805105310562
S.D.0.0778719124784401
T-STAT0.110155905770011
p-value0.916570536273938

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.459142738411067 \tabularnewline
beta & 0.00857805105310562 \tabularnewline
S.D. & 0.0778719124784401 \tabularnewline
T-STAT & 0.110155905770011 \tabularnewline
p-value & 0.916570536273938 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41703&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.459142738411067[/C][/ROW]
[ROW][C]beta[/C][C]0.00857805105310562[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0778719124784401[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.110155905770011[/C][/ROW]
[ROW][C]p-value[/C][C]0.916570536273938[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41703&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41703&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.459142738411067
beta0.00857805105310562
S.D.0.0778719124784401
T-STAT0.110155905770011
p-value0.916570536273938






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.17441609433129
beta0.286328983796835
S.D.0.50935533928031
T-STAT0.562139947725691
p-value0.598286400037338
Lambda0.713671016203165

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.17441609433129 \tabularnewline
beta & 0.286328983796835 \tabularnewline
S.D. & 0.50935533928031 \tabularnewline
T-STAT & 0.562139947725691 \tabularnewline
p-value & 0.598286400037338 \tabularnewline
Lambda & 0.713671016203165 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41703&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.17441609433129[/C][/ROW]
[ROW][C]beta[/C][C]0.286328983796835[/C][/ROW]
[ROW][C]S.D.[/C][C]0.50935533928031[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.562139947725691[/C][/ROW]
[ROW][C]p-value[/C][C]0.598286400037338[/C][/ROW]
[ROW][C]Lambda[/C][C]0.713671016203165[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41703&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41703&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.17441609433129
beta0.286328983796835
S.D.0.50935533928031
T-STAT0.562139947725691
p-value0.598286400037338
Lambda0.713671016203165


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.1 ; par2 = 0.9 ; par3 = 0.1 ;
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')