FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationThu, 03 Dec 2009 12:23:58 -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/Dec/03/t1259868404df7q3nvt6xqhcbk.htm/, Retrieved Sat, 20 Apr 2024 09:49:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63084, Retrieved Sat, 20 Apr 2024 09:49:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
- R  D      [Standard Deviation-Mean Plot] [] [2009-12-03 19:23:58] [ed082d38031561faed979d8cebfeba4d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1915
1843
1761
2858
3968
5061
4661
4269
3857
3568
3274
2987
1683
1381
1071
2772
4485
6181
5479
4782
4067
3489
2903
2330
1736
1483
1242
2334
3423
4523
3986
3462
2908
2575
2237
1904
1610
1251
941
2450
3946
5409
4741
4069
3539
3189
2960
2704
1697
1598
1456
2316
3083
4158
3469
2892
2578
2233
1947
2049

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=63084&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=63084&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63084&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
13335.166666666671104.102418942713300
23385.251646.719445387765110
32651.083333333331028.182992055173281
43067.416666666671373.980247200444468
52456.33333333333816.1653501514742702

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3335.16666666667 & 1104.10241894271 & 3300 \tabularnewline
2 & 3385.25 & 1646.71944538776 & 5110 \tabularnewline
3 & 2651.08333333333 & 1028.18299205517 & 3281 \tabularnewline
4 & 3067.41666666667 & 1373.98024720044 & 4468 \tabularnewline
5 & 2456.33333333333 & 816.165350151474 & 2702 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63084&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]3335.16666666667[/C][C]1104.10241894271[/C][C]3300[/C][/ROW]
[ROW][C]2[/C][C]3385.25[/C][C]1646.71944538776[/C][C]5110[/C][/ROW]
[ROW][C]3[/C][C]2651.08333333333[/C][C]1028.18299205517[/C][C]3281[/C][/ROW]
[ROW][C]4[/C][C]3067.41666666667[/C][C]1373.98024720044[/C][C]4468[/C][/ROW]
[ROW][C]5[/C][C]2456.33333333333[/C][C]816.165350151474[/C][C]2702[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63084&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63084&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
13335.166666666671104.102418942713300
23385.251646.719445387765110
32651.083333333331028.182992055173281
43067.416666666671373.980247200444468
52456.33333333333816.1653501514742702






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-643.578297236554
beta0.616776619386739
S.D.0.277192851120948
T-STAT2.22508126343280
p-value0.112509904118504

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -643.578297236554 \tabularnewline
beta & 0.616776619386739 \tabularnewline
S.D. & 0.277192851120948 \tabularnewline
T-STAT & 2.22508126343280 \tabularnewline
p-value & 0.112509904118504 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63084&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-643.578297236554[/C][/ROW]
[ROW][C]beta[/C][C]0.616776619386739[/C][/ROW]
[ROW][C]S.D.[/C][C]0.277192851120948[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.22508126343280[/C][/ROW]
[ROW][C]p-value[/C][C]0.112509904118504[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63084&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63084&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)
alpha-643.578297236554
beta0.616776619386739
S.D.0.277192851120948
T-STAT2.22508126343280
p-value0.112509904118504






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.46293632129809
beta1.56651721096340
S.D.0.625891710379603
T-STAT2.50285662037817
p-value0.0874861053044273
Lambda-0.566517210963404

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.46293632129809 \tabularnewline
beta & 1.56651721096340 \tabularnewline
S.D. & 0.625891710379603 \tabularnewline
T-STAT & 2.50285662037817 \tabularnewline
p-value & 0.0874861053044273 \tabularnewline
Lambda & -0.566517210963404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63084&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.46293632129809[/C][/ROW]
[ROW][C]beta[/C][C]1.56651721096340[/C][/ROW]
[ROW][C]S.D.[/C][C]0.625891710379603[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.50285662037817[/C][/ROW]
[ROW][C]p-value[/C][C]0.0874861053044273[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.566517210963404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63084&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63084&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-5.46293632129809
beta1.56651721096340
S.D.0.625891710379603
T-STAT2.50285662037817
p-value0.0874861053044273
Lambda-0.566517210963404


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')