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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 computationSun, 06 Aug 2017 19:00:58 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/06/t1502038887q5voabks17dsaw6.htm/, Retrieved Sat, 11 May 2024 19:10:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306970, Retrieved Sat, 11 May 2024 19:10:22 +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)
-       [Standard Deviation-Mean Plot] [] [2017-08-06 17:00:58] [bb1ebaef39f3ee233240b5c77a617fca] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1755000.00
1690000.00
1787500.00
1430000.00
1852500.00
1820000.00
1950000.00
2015000.00
2242500.00
1950000.00
1852500.00
2307500.00
1950000.00
1462500.00
1722500.00
1300000.00
1820000.00
1495000.00
1982500.00
1787500.00
1885000.00
2112500.00
2080000.00
2470000.00
1787500.00
1495000.00
1657500.00
1202500.00
1722500.00
1332500.00
1885000.00
1787500.00
1592500.00
2275000.00
2047500.00
2340000.00
1755000.00
1625000.00
1462500.00
1202500.00
1592500.00
1430000.00
1950000.00
1885000.00
1625000.00
2177500.00
2015000.00
2600000.00
2080000.00
1267500.00
1267500.00
1267500.00
1495000.00
1495000.00
2015000.00
1852500.00
1657500.00
2080000.00
1917500.00
2762500.00
2177500.00
1267500.00
1332500.00
1105000.00
1527500.00
1755000.00
2210000.00
2177500.00
1755000.00
2047500.00
1820000.00
2600000.00
1982500.00
1592500.00
1430000.00
1072500.00
1592500.00
1917500.00
2242500.00
2112500.00
1560000.00
2242500.00
1755000.00
2697500.00
2242500.00
1625000.00
1495000.00
1007500.00
1592500.00
1527500.00
2307500.00
2307500.00
1755000.00
2275000.00
1690000.00
2632500.00
2242500.00
1657500.00
1267500.00
877500.00
1722500.00
1657500.00
2177500.00
2502500.00
1852500.00
2080000.00
1560000.00
2697500.00

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306970&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306970&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11887708.33333333235365.910323531877500
21838958.33333333320974.118068261170000
31760416.66666667344459.1170710011137500
41776666.66666667377319.091711111397500
51763125445859.9007943681495000
61814583.33333333448802.4891223581495000
71849791.66666667439424.2854594121625000
81871458.33333333472081.293959061625000
91857916.66666667514958.993660191820000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1887708.33333333 & 235365.910323531 & 877500 \tabularnewline
2 & 1838958.33333333 & 320974.11806826 & 1170000 \tabularnewline
3 & 1760416.66666667 & 344459.117071001 & 1137500 \tabularnewline
4 & 1776666.66666667 & 377319.09171111 & 1397500 \tabularnewline
5 & 1763125 & 445859.900794368 & 1495000 \tabularnewline
6 & 1814583.33333333 & 448802.489122358 & 1495000 \tabularnewline
7 & 1849791.66666667 & 439424.285459412 & 1625000 \tabularnewline
8 & 1871458.33333333 & 472081.29395906 & 1625000 \tabularnewline
9 & 1857916.66666667 & 514958.99366019 & 1820000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306970&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]1887708.33333333[/C][C]235365.910323531[/C][C]877500[/C][/ROW]
[ROW][C]2[/C][C]1838958.33333333[/C][C]320974.11806826[/C][C]1170000[/C][/ROW]
[ROW][C]3[/C][C]1760416.66666667[/C][C]344459.117071001[/C][C]1137500[/C][/ROW]
[ROW][C]4[/C][C]1776666.66666667[/C][C]377319.09171111[/C][C]1397500[/C][/ROW]
[ROW][C]5[/C][C]1763125[/C][C]445859.900794368[/C][C]1495000[/C][/ROW]
[ROW][C]6[/C][C]1814583.33333333[/C][C]448802.489122358[/C][C]1495000[/C][/ROW]
[ROW][C]7[/C][C]1849791.66666667[/C][C]439424.285459412[/C][C]1625000[/C][/ROW]
[ROW][C]8[/C][C]1871458.33333333[/C][C]472081.29395906[/C][C]1625000[/C][/ROW]
[ROW][C]9[/C][C]1857916.66666667[/C][C]514958.99366019[/C][C]1820000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306970&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
11887708.33333333235365.910323531877500
21838958.33333333320974.118068261170000
31760416.66666667344459.1170710011137500
41776666.66666667377319.091711111397500
51763125445859.9007943681495000
61814583.33333333448802.4891223581495000
71849791.66666667439424.2854594121625000
81871458.33333333472081.293959061625000
91857916.66666667514958.993660191820000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha595957.08016558
beta-0.107448317059852
S.D.0.688757001617613
T-STAT-0.156003230177696
p-value0.880434120508995

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 595957.08016558 \tabularnewline
beta & -0.107448317059852 \tabularnewline
S.D. & 0.688757001617613 \tabularnewline
T-STAT & -0.156003230177696 \tabularnewline
p-value & 0.880434120508995 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306970&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]595957.08016558[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059852[/C][/ROW]
[ROW][C]S.D.[/C][C]0.688757001617613[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177696[/C][/ROW]
[ROW][C]p-value[/C][C]0.880434120508995[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306970&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306970&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)
alpha595957.08016558
beta-0.107448317059852
S.D.0.688757001617613
T-STAT-0.156003230177696
p-value0.880434120508995






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha31.5631582024568
beta-1.29633550728143
S.D.3.45582772786272
T-STAT-0.375115778147646
p-value0.718681736243561
Lambda2.29633550728143

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 31.5631582024568 \tabularnewline
beta & -1.29633550728143 \tabularnewline
S.D. & 3.45582772786272 \tabularnewline
T-STAT & -0.375115778147646 \tabularnewline
p-value & 0.718681736243561 \tabularnewline
Lambda & 2.29633550728143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306970&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]31.5631582024568[/C][/ROW]
[ROW][C]beta[/C][C]-1.29633550728143[/C][/ROW]
[ROW][C]S.D.[/C][C]3.45582772786272[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147646[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243561[/C][/ROW]
[ROW][C]Lambda[/C][C]2.29633550728143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306970&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306970&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)
alpha31.5631582024568
beta-1.29633550728143
S.D.3.45582772786272
T-STAT-0.375115778147646
p-value0.718681736243561
Lambda2.29633550728143


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')