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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 computationFri, 07 Aug 2015 14:11:33 +0100
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/Aug/07/t143895325764ertv54gc8tvbg.htm/, Retrieved Wed, 15 May 2024 17:51:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279894, Retrieved Wed, 15 May 2024 17:51:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2015-08-07 13:11:33] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1684800.00
1622400.00
1716000.00
1372800.00
1778400.00
1747200.00
1872000.00
1934400.00
2152800.00
1872000.00
1778400.00
2215200.00
1872000.00
1404000.00
1653600.00
1248000.00
1747200.00
1435200.00
1903200.00
1716000.00
1809600.00
2028000.00
1996800.00
2371200.00
1716000.00
1435200.00
1591200.00
1154400.00
1653600.00
1279200.00
1809600.00
1716000.00
1528800.00
2184000.00
1965600.00
2246400.00
1684800.00
1560000.00
1404000.00
1154400.00
1528800.00
1372800.00
1872000.00
1809600.00
1560000.00
2090400.00
1934400.00
2496000.00
1996800.00
1216800.00
1216800.00
1216800.00
1435200.00
1435200.00
1934400.00
1778400.00
1591200.00
1996800.00
1840800.00
2652000.00
2090400.00
1216800.00
1279200.00
1060800.00
1466400.00
1684800.00
2121600.00
2090400.00
1684800.00
1965600.00
1747200.00
2496000.00
1903200.00
1528800.00
1372800.00
1029600.00
1528800.00
1840800.00
2152800.00
2028000.00
1497600.00
2152800.00
1684800.00
2589600.00
2152800.00
1560000.00
1435200.00
967200.00
1528800.00
1466400.00
2215200.00
2215200.00
1684800.00
2184000.00
1622400.00
2527200.00
2152800.00
1591200.00
1216800.00
842400.00
1653600.00
1591200.00
2090400.00
2402400.00
1778400.00
1996800.00
1497600.00
2589600.00

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'Gertrude Mary Cox' @ cox.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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279894&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279894&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279894&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11812200225951.273910589842400
21765400308135.1533455291123200
31690000330680.7523881611092000
41705600362226.3280426651341600
51692600428025.5047625931435200
61742000430850.3895574641435200
71775800421847.3140410361560000
81796600453198.0422006981560000
91783600494360.6339137821747200

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1812200 & 225951.273910589 & 842400 \tabularnewline
2 & 1765400 & 308135.153345529 & 1123200 \tabularnewline
3 & 1690000 & 330680.752388161 & 1092000 \tabularnewline
4 & 1705600 & 362226.328042665 & 1341600 \tabularnewline
5 & 1692600 & 428025.504762593 & 1435200 \tabularnewline
6 & 1742000 & 430850.389557464 & 1435200 \tabularnewline
7 & 1775800 & 421847.314041036 & 1560000 \tabularnewline
8 & 1796600 & 453198.042200698 & 1560000 \tabularnewline
9 & 1783600 & 494360.633913782 & 1747200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279894&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]1812200[/C][C]225951.273910589[/C][C]842400[/C][/ROW]
[ROW][C]2[/C][C]1765400[/C][C]308135.153345529[/C][C]1123200[/C][/ROW]
[ROW][C]3[/C][C]1690000[/C][C]330680.752388161[/C][C]1092000[/C][/ROW]
[ROW][C]4[/C][C]1705600[/C][C]362226.328042665[/C][C]1341600[/C][/ROW]
[ROW][C]5[/C][C]1692600[/C][C]428025.504762593[/C][C]1435200[/C][/ROW]
[ROW][C]6[/C][C]1742000[/C][C]430850.389557464[/C][C]1435200[/C][/ROW]
[ROW][C]7[/C][C]1775800[/C][C]421847.314041036[/C][C]1560000[/C][/ROW]
[ROW][C]8[/C][C]1796600[/C][C]453198.042200698[/C][C]1560000[/C][/ROW]
[ROW][C]9[/C][C]1783600[/C][C]494360.633913782[/C][C]1747200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279894&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279894&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
11812200225951.273910589842400
21765400308135.1533455291123200
31690000330680.7523881611092000
41705600362226.3280426651341600
51692600428025.5047625931435200
61742000430850.3895574641435200
71775800421847.3140410361560000
81796600453198.0422006981560000
91783600494360.6339137821747200






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha572118.79695898
beta-0.107448317059865
S.D.0.68875700161761
T-STAT-0.156003230177716
p-value0.88043412050898

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 572118.79695898 \tabularnewline
beta & -0.107448317059865 \tabularnewline
S.D. & 0.68875700161761 \tabularnewline
T-STAT & -0.156003230177716 \tabularnewline
p-value & 0.88043412050898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279894&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]572118.79695898[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059865[/C][/ROW]
[ROW][C]S.D.[/C][C]0.68875700161761[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177716[/C][/ROW]
[ROW][C]p-value[/C][C]0.88043412050898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279894&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279894&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)
alpha572118.79695898
beta-0.107448317059865
S.D.0.68875700161761
T-STAT-0.156003230177716
p-value0.88043412050898






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha31.4694172069629
beta-1.2963355072815
S.D.3.4558277278626
T-STAT-0.375115778147677
p-value0.718681736243539
Lambda2.2963355072815

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 31.4694172069629 \tabularnewline
beta & -1.2963355072815 \tabularnewline
S.D. & 3.4558277278626 \tabularnewline
T-STAT & -0.375115778147677 \tabularnewline
p-value & 0.718681736243539 \tabularnewline
Lambda & 2.2963355072815 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279894&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]31.4694172069629[/C][/ROW]
[ROW][C]beta[/C][C]-1.2963355072815[/C][/ROW]
[ROW][C]S.D.[/C][C]3.4558277278626[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147677[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243539[/C][/ROW]
[ROW][C]Lambda[/C][C]2.2963355072815[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279894&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279894&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)
alpha31.4694172069629
beta-1.2963355072815
S.D.3.4558277278626
T-STAT-0.375115778147677
p-value0.718681736243539
Lambda2.2963355072815


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')