FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 01 Aug 2017 02:51:32 +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/01/t1501548711g6mk23np1md6geq.htm/, Retrieved Fri, 10 May 2024 07:36:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306852, Retrieved Fri, 10 May 2024 07:36:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

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] [Reeks B stap 21] [2017-08-01 00:51:32] [5e513ceaaef205c0c6f269c0b513af8d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1755000
1690000
1787500
1430000
1852500
1820000
1950000
2015000
2242500
1950000
1852500
2307500
1950000
1462500
1722500
1300000
1820000
1495000
1982500
1787500
1885000
2112500
2080000
2470000
1787500
1495000
1657500
1202500
1722500
1332500
1885000
1787500
1592500
2275000
2047500
2340000
1755000
1625000
1462500
1202500
1592500
1430000
1950000
1885000
1625000
2177500
2015000
2600000
2080000
1267500
1267500
1267500
1495000
1495000
2015000
1852500
1657500
2080000
1917500
2762500
2177500
1267500
1332500
1105000
1527500
1755000
2210000
2177500
1755000
2047500
1820000
2600000
1982500
1592500
1430000
1072500
1592500
1917500
2242500
2112500
1560000
2242500
1755000
2697500
2242500
1625000
1495000
1007500
1592500
1527500
2307500
2307500
1755000
2275000
1690000
2632500
2242500
1657500
1267500
877500
1722500
1657500
2177500
2502500
1852500
2080000
1560000
2697500

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=306852&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=306852&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306852&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=306852&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=306852&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306852&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=306852&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=306852&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306852&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=306852&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=306852&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306852&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')