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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, 12 Dec 2009 08:31:03 -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/12/t12606319291kknshgeluufrx8.htm/, Retrieved Mon, 29 Apr 2024 11:35:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67019, Retrieved Mon, 29 Apr 2024 11:35:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [Paper] [2009-12-12 13:34:31] [d31db4f83c6a129f6d3e47077769e868]
-    D  [Bivariate Kernel Density Estimation] [Paper.1] [2009-12-12 13:38:38] [d31db4f83c6a129f6d3e47077769e868]
- RMPD    [Standard Deviation-Mean Plot] [Paper. Mean Plot ...] [2009-12-12 14:46:45] [d31db4f83c6a129f6d3e47077769e868]
-    D      [Standard Deviation-Mean Plot] [Paper] [2009-12-12 14:54:21] [d31db4f83c6a129f6d3e47077769e868]
-    D        [Standard Deviation-Mean Plot] [Paper. Ingeschrev...] [2009-12-12 15:28:35] [d31db4f83c6a129f6d3e47077769e868]
-    D            [Standard Deviation-Mean Plot] [Paper. achtergest...] [2009-12-12 15:31:03] [852eae237d08746109043531619a60c9] [Current]
- RM D              [(Partial) Autocorrelation Function] [Paper, Partiële ...] [2009-12-12 15:59:27] [d31db4f83c6a129f6d3e47077769e868]
- RM D              [Spectral Analysis] [Paper. Spectral A...] [2009-12-12 16:10:11] [d31db4f83c6a129f6d3e47077769e868]
-   P                 [Spectral Analysis] [Paper. Spectral A...] [2009-12-18 15:52:57] [d31db4f83c6a129f6d3e47077769e868]
-   P                   [Spectral Analysis] [Paper. Spectral A...] [2009-12-18 17:24:57] [d31db4f83c6a129f6d3e47077769e868]
-   P                     [Spectral Analysis] [Paper] [2010-01-07 15:25:28] [309ee52d0058ff0a6f7eec15e07b2d9f]
- RM D              [Mean Plot] [Paper. Mean plot] [2009-12-12 16:13:07] [d31db4f83c6a129f6d3e47077769e868]
-    D                [Mean Plot] [Paper. Mean plot ...] [2009-12-12 16:15:50] [d31db4f83c6a129f6d3e47077769e868]
-    D                [Mean Plot] [Paper. Inschrijvi...] [2009-12-12 16:18:27] [d31db4f83c6a129f6d3e47077769e868]
-    D                  [Mean Plot] [Paper. Mean plot ...] [2009-12-12 16:20:40] [d31db4f83c6a129f6d3e47077769e868]
- RM D                  [ARIMA Backward Selection] [Paper. Arima back...] [2009-12-12 17:23:23] [d31db4f83c6a129f6d3e47077769e868]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
707 169
703 434
701 017
696 968
688 558
679 237
677 362
676 693
670 009
667 209
662 976
660 194
652 270
648 024
629 295
624 961
617 306
607 691
596 219
591 130
584 528
576 798
575 683
574 369
566 815
573 074
567 739
571 942
570 274
568 800
558 115
550 591
548 872
547 009
545 946
539 702
542 427
542 968
536 640
533 653
540 996
538 316
532 646
533 390
528 715
530 664
528 564
519 107
518 703
519 059
518 498
524 575
536 046
552 006
560 687
578 884
591 491
599 228
633 019
649 918
655 509

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' @ 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67019&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67019&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67019&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' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1682568.83333333316445.469599051746975
2606522.83333333327776.281545864877901
3559073.2512010.489984138533372
4534007.1666666676867.0338950052923861
5565176.16666666745706.3329903444131420

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 682568.833333333 & 16445.4695990517 & 46975 \tabularnewline
2 & 606522.833333333 & 27776.2815458648 & 77901 \tabularnewline
3 & 559073.25 & 12010.4899841385 & 33372 \tabularnewline
4 & 534007.166666667 & 6867.03389500529 & 23861 \tabularnewline
5 & 565176.166666667 & 45706.3329903444 & 131420 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67019&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]682568.833333333[/C][C]16445.4695990517[/C][C]46975[/C][/ROW]
[ROW][C]2[/C][C]606522.833333333[/C][C]27776.2815458648[/C][C]77901[/C][/ROW]
[ROW][C]3[/C][C]559073.25[/C][C]12010.4899841385[/C][C]33372[/C][/ROW]
[ROW][C]4[/C][C]534007.166666667[/C][C]6867.03389500529[/C][C]23861[/C][/ROW]
[ROW][C]5[/C][C]565176.166666667[/C][C]45706.3329903444[/C][C]131420[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67019&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67019&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
1682568.83333333316445.469599051746975
2606522.83333333327776.281545864877901
3559073.2512010.489984138533372
4534007.1666666676867.0338950052923861
5565176.16666666745706.3329903444131420






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha15303.2263365861
beta0.0109554330172806
S.D.0.153130643529442
T-STAT0.071543048241512
p-value0.9474680609667

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 15303.2263365861 \tabularnewline
beta & 0.0109554330172806 \tabularnewline
S.D. & 0.153130643529442 \tabularnewline
T-STAT & 0.071543048241512 \tabularnewline
p-value & 0.9474680609667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67019&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15303.2263365861[/C][/ROW]
[ROW][C]beta[/C][C]0.0109554330172806[/C][/ROW]
[ROW][C]S.D.[/C][C]0.153130643529442[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.071543048241512[/C][/ROW]
[ROW][C]p-value[/C][C]0.9474680609667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67019&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67019&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)
alpha15303.2263365861
beta0.0109554330172806
S.D.0.153130643529442
T-STAT0.071543048241512
p-value0.9474680609667






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-17.8880118847823
beta2.08289240175418
S.D.4.26509635946727
T-STAT0.488357642173962
p-value0.658766305878218
Lambda-1.08289240175418

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -17.8880118847823 \tabularnewline
beta & 2.08289240175418 \tabularnewline
S.D. & 4.26509635946727 \tabularnewline
T-STAT & 0.488357642173962 \tabularnewline
p-value & 0.658766305878218 \tabularnewline
Lambda & -1.08289240175418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67019&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-17.8880118847823[/C][/ROW]
[ROW][C]beta[/C][C]2.08289240175418[/C][/ROW]
[ROW][C]S.D.[/C][C]4.26509635946727[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.488357642173962[/C][/ROW]
[ROW][C]p-value[/C][C]0.658766305878218[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.08289240175418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67019&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67019&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-17.8880118847823
beta2.08289240175418
S.D.4.26509635946727
T-STAT0.488357642173962
p-value0.658766305878218
Lambda-1.08289240175418


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')