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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 computationWed, 27 Nov 2013 12:11:09 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/27/t1385572419p4audcjrd866i2x.htm/, Retrieved Mon, 29 Apr 2024 08:14:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=229071, Retrieved Mon, 29 Apr 2024 08:14:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

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] [Reserve positie I...] [2013-11-27 17:11:09] [a3fde7297e5409122ee2dd3b0c427a94] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
679
687
638
628
604
713
712
693
697
555
486
470
465
426
384
379
381
380
351
346
339
336
333
324
324
321
304
343
407
389
361
353
361
387
692
704
742
721
843
847
945
946
946
945
1082
1075
820
832
851
1090
1203
1239
1535
1527
1480
1452
1383
1381
1429
1376
1602
1597
2003
1958
1997
1986
2129
2115
2297
2250
2309
2648
2627
2711
2732
2825
2932
2910
2969
2999
2965
2846
2847
2751

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229071&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229071&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229071&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'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1630.16666666666785.5068666390264243
2370.33333333333341.7750106541161141
3412.166666666667136.839543283587400
4895.333333333333115.150757573266361
51328.83333333333201.580046511343684
62074.25294.2778912401121051
72842.83333333333117.828714923851372

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 630.166666666667 & 85.5068666390264 & 243 \tabularnewline
2 & 370.333333333333 & 41.7750106541161 & 141 \tabularnewline
3 & 412.166666666667 & 136.839543283587 & 400 \tabularnewline
4 & 895.333333333333 & 115.150757573266 & 361 \tabularnewline
5 & 1328.83333333333 & 201.580046511343 & 684 \tabularnewline
6 & 2074.25 & 294.277891240112 & 1051 \tabularnewline
7 & 2842.83333333333 & 117.828714923851 & 372 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229071&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]630.166666666667[/C][C]85.5068666390264[/C][C]243[/C][/ROW]
[ROW][C]2[/C][C]370.333333333333[/C][C]41.7750106541161[/C][C]141[/C][/ROW]
[ROW][C]3[/C][C]412.166666666667[/C][C]136.839543283587[/C][C]400[/C][/ROW]
[ROW][C]4[/C][C]895.333333333333[/C][C]115.150757573266[/C][C]361[/C][/ROW]
[ROW][C]5[/C][C]1328.83333333333[/C][C]201.580046511343[/C][C]684[/C][/ROW]
[ROW][C]6[/C][C]2074.25[/C][C]294.277891240112[/C][C]1051[/C][/ROW]
[ROW][C]7[/C][C]2842.83333333333[/C][C]117.828714923851[/C][C]372[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229071&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229071&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
1630.16666666666785.5068666390264243
2370.33333333333341.7750106541161141
3412.166666666667136.839543283587400
4895.333333333333115.150757573266361
51328.83333333333201.580046511343684
62074.25294.2778912401121051
72842.83333333333117.828714923851372






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha88.1360374973498
beta0.0439572400569546
S.D.0.0346604986061758
T-STAT1.26822295767904
p-value0.260560598999383

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 88.1360374973498 \tabularnewline
beta & 0.0439572400569546 \tabularnewline
S.D. & 0.0346604986061758 \tabularnewline
T-STAT & 1.26822295767904 \tabularnewline
p-value & 0.260560598999383 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229071&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]88.1360374973498[/C][/ROW]
[ROW][C]beta[/C][C]0.0439572400569546[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0346604986061758[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.26822295767904[/C][/ROW]
[ROW][C]p-value[/C][C]0.260560598999383[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229071&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229071&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)
alpha88.1360374973498
beta0.0439572400569546
S.D.0.0346604986061758
T-STAT1.26822295767904
p-value0.260560598999383






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.29922058773186
beta0.511068483786484
S.D.0.271726620483369
T-STAT1.88081860686801
p-value0.11875177531302
Lambda0.488931516213516

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.29922058773186 \tabularnewline
beta & 0.511068483786484 \tabularnewline
S.D. & 0.271726620483369 \tabularnewline
T-STAT & 1.88081860686801 \tabularnewline
p-value & 0.11875177531302 \tabularnewline
Lambda & 0.488931516213516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229071&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.29922058773186[/C][/ROW]
[ROW][C]beta[/C][C]0.511068483786484[/C][/ROW]
[ROW][C]S.D.[/C][C]0.271726620483369[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.88081860686801[/C][/ROW]
[ROW][C]p-value[/C][C]0.11875177531302[/C][/ROW]
[ROW][C]Lambda[/C][C]0.488931516213516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229071&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229071&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)
alpha1.29922058773186
beta0.511068483786484
S.D.0.271726620483369
T-STAT1.88081860686801
p-value0.11875177531302
Lambda0.488931516213516


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')