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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 computationThu, 29 Nov 2007 01:51:49 -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/2007/Nov/29/t1196325708gtnalnu23zl90h1.htm/, Retrieved Fri, 03 May 2024 10:42:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7288, Retrieved Fri, 03 May 2024 10:42:57 +0000
QR Codes:

Original text written by user:Inducing Stationary in Time Series (vraag 1)
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact258

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] [Standard Deviatio...] [2007-11-29 08:51:49] [0eafefa7b02d47065fceb6c46f54fbf9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7288&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7288&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1527.529.598832900824161
2565.58333333333326.1376020786958104
3595.91666666666721.9191005677005117
4596.08333333333319.4303339854949107

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 527.5 & 29.5988329008241 & 61 \tabularnewline
2 & 565.583333333333 & 26.1376020786958 & 104 \tabularnewline
3 & 595.916666666667 & 21.9191005677005 & 117 \tabularnewline
4 & 596.083333333333 & 19.4303339854949 & 107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7288&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]527.5[/C][C]29.5988329008241[/C][C]61[/C][/ROW]
[ROW][C]2[/C][C]565.583333333333[/C][C]26.1376020786958[/C][C]104[/C][/ROW]
[ROW][C]3[/C][C]595.916666666667[/C][C]21.9191005677005[/C][C]117[/C][/ROW]
[ROW][C]4[/C][C]596.083333333333[/C][C]19.4303339854949[/C][C]107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7288&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
1527.529.598832900824161
2565.58333333333326.1376020786958104
3595.91666666666721.9191005677005117
4596.08333333333319.4303339854949107






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha100.270159293422
beta-0.133034433889781
S.D.0.0272422579338418
T-STAT-4.88338500475463
p-value0.0394673741580635

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 100.270159293422 \tabularnewline
beta & -0.133034433889781 \tabularnewline
S.D. & 0.0272422579338418 \tabularnewline
T-STAT & -4.88338500475463 \tabularnewline
p-value & 0.0394673741580635 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7288&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]100.270159293422[/C][/ROW]
[ROW][C]beta[/C][C]-0.133034433889781[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0272422579338418[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.88338500475463[/C][/ROW]
[ROW][C]p-value[/C][C]0.0394673741580635[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7288&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7288&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)
alpha100.270159293422
beta-0.133034433889781
S.D.0.0272422579338418
T-STAT-4.88338500475463
p-value0.0394673741580635






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha22.3855156283425
beta-3.02667936008226
S.D.0.776197217475001
T-STAT-3.89936899017515
p-value0.059917422248785
Lambda4.02667936008226

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 22.3855156283425 \tabularnewline
beta & -3.02667936008226 \tabularnewline
S.D. & 0.776197217475001 \tabularnewline
T-STAT & -3.89936899017515 \tabularnewline
p-value & 0.059917422248785 \tabularnewline
Lambda & 4.02667936008226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7288&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22.3855156283425[/C][/ROW]
[ROW][C]beta[/C][C]-3.02667936008226[/C][/ROW]
[ROW][C]S.D.[/C][C]0.776197217475001[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.89936899017515[/C][/ROW]
[ROW][C]p-value[/C][C]0.059917422248785[/C][/ROW]
[ROW][C]Lambda[/C][C]4.02667936008226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7288&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7288&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)
alpha22.3855156283425
beta-3.02667936008226
S.D.0.776197217475001
T-STAT-3.89936899017515
p-value0.059917422248785
Lambda4.02667936008226


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')