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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 25 Nov 2009 15:25:35 -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/2009/Nov/25/t12591879811kj9skhec74xqva.htm/, Retrieved Tue, 07 May 2024 06:07:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59671, Retrieved Tue, 07 May 2024 06:07:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
- R  D          [Standard Deviation-Mean Plot] [WS08 - Heteroskel...] [2009-11-25 22:25:35] [0cc924834281808eda7297686c82928f] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
518.1
523.3
536.1
538.2
561.2
562
577.6
606.9
607.3
617.2
625.2
637.3
652.9
653.9
670.4
677.2
710
729.9
742.6
748.2
808.4
844.3
854.2
1446
1527.6
1544.1
1596.1
1620.1
1625.4
1656.5
1667.6
1672.9
1685.1
1726.5
1755.9
1758.2
1795
1801.2
1819
1837.3
1851.8
1858.1
1881.2
1898.4
1936.5
1936.5
1954.9
1963.5
1964.1
1966.1
1981.8
1983.5
2004.7
2058.6
2083.1
2085.2
2086.9
2098.9
2100.2
2117.9
2130.6
2133.3
2144.6
2164.4
2230.2
2235
2236.6
2255.3
2288.6
2292.5
2337
2338.4
2365.4
2371.2
2385.4
2386
2390
2405
2407.2
2432.6
2432.6
2448.3
2471.9
2477.9
2490
2515.7
2535.8
2543.8
2560.8
2573.7
2584.3
2605.1
2607.3
2607.3
2668.6
2671.2
2685.9
2705.6
2724.5
2727.3
2735.6
2790.7
2798.7
2812.3
2812.3
2839.3
2862.5
2862.5
2862.9
2862.9
2866
2887.2
2934.9
3053.2

Tables (Output of Computation)





Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59671&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59671&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1575.86666666666741.9720758542528119.2
2794.833333333333216.546863848046793.1
3165374.696768823874230.6
41877.7833333333359.9252387765309168.5
52044.2559.1137039949283153.800000000000
62232.2083333333375.0864405908687207.8
72414.4583333333337.8999990005597112.5
82580.355.7692486134526181.200
92779.7666666666761.7164827450839176.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 575.866666666667 & 41.9720758542528 & 119.2 \tabularnewline
2 & 794.833333333333 & 216.546863848046 & 793.1 \tabularnewline
3 & 1653 & 74.696768823874 & 230.6 \tabularnewline
4 & 1877.78333333333 & 59.9252387765309 & 168.5 \tabularnewline
5 & 2044.25 & 59.1137039949283 & 153.800000000000 \tabularnewline
6 & 2232.20833333333 & 75.0864405908687 & 207.8 \tabularnewline
7 & 2414.45833333333 & 37.8999990005597 & 112.5 \tabularnewline
8 & 2580.3 & 55.7692486134526 & 181.200 \tabularnewline
9 & 2779.76666666667 & 61.7164827450839 & 176.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59671&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]575.866666666667[/C][C]41.9720758542528[/C][C]119.2[/C][/ROW]
[ROW][C]2[/C][C]794.833333333333[/C][C]216.546863848046[/C][C]793.1[/C][/ROW]
[ROW][C]3[/C][C]1653[/C][C]74.696768823874[/C][C]230.6[/C][/ROW]
[ROW][C]4[/C][C]1877.78333333333[/C][C]59.9252387765309[/C][C]168.5[/C][/ROW]
[ROW][C]5[/C][C]2044.25[/C][C]59.1137039949283[/C][C]153.800000000000[/C][/ROW]
[ROW][C]6[/C][C]2232.20833333333[/C][C]75.0864405908687[/C][C]207.8[/C][/ROW]
[ROW][C]7[/C][C]2414.45833333333[/C][C]37.8999990005597[/C][C]112.5[/C][/ROW]
[ROW][C]8[/C][C]2580.3[/C][C]55.7692486134526[/C][C]181.200[/C][/ROW]
[ROW][C]9[/C][C]2779.76666666667[/C][C]61.7164827450839[/C][C]176.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59671&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
1575.86666666666741.9720758542528119.2
2794.833333333333216.546863848046793.1
3165374.696768823874230.6
41877.7833333333359.9252387765309168.5
52044.2559.1137039949283153.800000000000
62232.2083333333375.0864405908687207.8
72414.4583333333337.8999990005597112.5
82580.355.7692486134526181.200
92779.7666666666761.7164827450839176.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha139.748756542626
beta-0.0339190749017468
S.D.0.0235741860682499
T-STAT-1.43882273617198
p-value0.193372308030808

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 139.748756542626 \tabularnewline
beta & -0.0339190749017468 \tabularnewline
S.D. & 0.0235741860682499 \tabularnewline
T-STAT & -1.43882273617198 \tabularnewline
p-value & 0.193372308030808 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59671&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]139.748756542626[/C][/ROW]
[ROW][C]beta[/C][C]-0.0339190749017468[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0235741860682499[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.43882273617198[/C][/ROW]
[ROW][C]p-value[/C][C]0.193372308030808[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59671&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59671&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)
alpha139.748756542626
beta-0.0339190749017468
S.D.0.0235741860682499
T-STAT-1.43882273617198
p-value0.193372308030808






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.37917525338755
beta-0.294725411775379
S.D.0.326959889059306
T-STAT-0.901411523668336
p-value0.397322589030081
Lambda1.29472541177538

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.37917525338755 \tabularnewline
beta & -0.294725411775379 \tabularnewline
S.D. & 0.326959889059306 \tabularnewline
T-STAT & -0.901411523668336 \tabularnewline
p-value & 0.397322589030081 \tabularnewline
Lambda & 1.29472541177538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59671&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.37917525338755[/C][/ROW]
[ROW][C]beta[/C][C]-0.294725411775379[/C][/ROW]
[ROW][C]S.D.[/C][C]0.326959889059306[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.901411523668336[/C][/ROW]
[ROW][C]p-value[/C][C]0.397322589030081[/C][/ROW]
[ROW][C]Lambda[/C][C]1.29472541177538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59671&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59671&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)
alpha6.37917525338755
beta-0.294725411775379
S.D.0.326959889059306
T-STAT-0.901411523668336
p-value0.397322589030081
Lambda1.29472541177538


Figures (Output of Computation)

Input Parameters & R Code

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')