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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 computationSat, 13 Dec 2008 06:44:05 -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/2008/Dec/13/t1229176001qzz0fk934myfeny.htm/, Retrieved Sun, 19 May 2024 07:13:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33083, Retrieved Sun, 19 May 2024 07:13:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Explorative Data Analysis] [Investigation Dis...] [2007-10-21 17:06:37] [b9964c45117f7aac638ab9056d451faa]
F    D  [Univariate Explorative Data Analysis] [Reproduce Q2] [2008-10-24 13:27:07] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
- RMPD      [Standard Deviation-Mean Plot] [Paper H5 Mannen S...] [2008-12-13 13:44:05] [5e9e099b83e50415d7642e10d74756e4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
269645
267037
258113
262813
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33083&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]0 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=33083&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33083&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1265696.4166666679003.5167417902330507
2277853.58088.0270827259926193
32819556962.8702415024220989
426243614819.413692242356928
5242686.59212.198676458629109

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 265696.416666667 & 9003.51674179023 & 30507 \tabularnewline
2 & 277853.5 & 8088.02708272599 & 26193 \tabularnewline
3 & 281955 & 6962.87024150242 & 20989 \tabularnewline
4 & 262436 & 14819.4136922423 & 56928 \tabularnewline
5 & 242686.5 & 9212.1986764586 & 29109 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33083&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]265696.416666667[/C][C]9003.51674179023[/C][C]30507[/C][/ROW]
[ROW][C]2[/C][C]277853.5[/C][C]8088.02708272599[/C][C]26193[/C][/ROW]
[ROW][C]3[/C][C]281955[/C][C]6962.87024150242[/C][C]20989[/C][/ROW]
[ROW][C]4[/C][C]262436[/C][C]14819.4136922423[/C][C]56928[/C][/ROW]
[ROW][C]5[/C][C]242686.5[/C][C]9212.1986764586[/C][C]29109[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33083&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33083&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
1265696.4166666679003.5167417902330507
2277853.58088.0270827259926193
32819556962.8702415024220989
426243614819.413692242356928
5242686.59212.198676458629109






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha29028.4773236966
beta-0.0729402979136698
S.D.0.105768017511402
T-STAT-0.689625272647346
p-value0.539985742651242

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 29028.4773236966 \tabularnewline
beta & -0.0729402979136698 \tabularnewline
S.D. & 0.105768017511402 \tabularnewline
T-STAT & -0.689625272647346 \tabularnewline
p-value & 0.539985742651242 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33083&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]29028.4773236966[/C][/ROW]
[ROW][C]beta[/C][C]-0.0729402979136698[/C][/ROW]
[ROW][C]S.D.[/C][C]0.105768017511402[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.689625272647346[/C][/ROW]
[ROW][C]p-value[/C][C]0.539985742651242[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33083&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33083&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)
alpha29028.4773236966
beta-0.0729402979136698
S.D.0.105768017511402
T-STAT-0.689625272647346
p-value0.539985742651242






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha34.6170855557133
beta-2.04000036790042
S.D.2.51585474797832
T-STAT-0.810857768931103
p-value0.476803190761904
Lambda3.04000036790042

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 34.6170855557133 \tabularnewline
beta & -2.04000036790042 \tabularnewline
S.D. & 2.51585474797832 \tabularnewline
T-STAT & -0.810857768931103 \tabularnewline
p-value & 0.476803190761904 \tabularnewline
Lambda & 3.04000036790042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33083&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]34.6170855557133[/C][/ROW]
[ROW][C]beta[/C][C]-2.04000036790042[/C][/ROW]
[ROW][C]S.D.[/C][C]2.51585474797832[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.810857768931103[/C][/ROW]
[ROW][C]p-value[/C][C]0.476803190761904[/C][/ROW]
[ROW][C]Lambda[/C][C]3.04000036790042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33083&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33083&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)
alpha34.6170855557133
beta-2.04000036790042
S.D.2.51585474797832
T-STAT-0.810857768931103
p-value0.476803190761904
Lambda3.04000036790042


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')