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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, 22 Nov 2007 06:03:14 -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/22/t1195736108kfz54i9syz8og3u.htm/, Retrieved Thu, 02 May 2024 17:22:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5964, Retrieved Thu, 02 May 2024 17:22:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsW10Q1G7
Estimated Impact201

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...] [2007-11-22 13:03:14] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
373
371
354
357
363
364
363
358
357
357
380
378
376
380
379
384
392
394
392
396
392
396
419
421
420
418
410
418
426
428
430
424
423
427
441
449
452
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418

Tables (Output of Computation)





Summary of compuational 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 compuational 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=5964&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]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=5964&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5964&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1364.5833333333338.85702939460917
2393.41666666666714.189998611911950
3426.16666666666710.477971119824695
4460.5833333333336.38831793671903115
5466.0833333333335.77547059606926113
6435.7517.1099386322687107

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 364.583333333333 & 8.8570293946091 & 7 \tabularnewline
2 & 393.416666666667 & 14.1899986119119 & 50 \tabularnewline
3 & 426.166666666667 & 10.4779711198246 & 95 \tabularnewline
4 & 460.583333333333 & 6.38831793671903 & 115 \tabularnewline
5 & 466.083333333333 & 5.77547059606926 & 113 \tabularnewline
6 & 435.75 & 17.1099386322687 & 107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5964&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]364.583333333333[/C][C]8.8570293946091[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]393.416666666667[/C][C]14.1899986119119[/C][C]50[/C][/ROW]
[ROW][C]3[/C][C]426.166666666667[/C][C]10.4779711198246[/C][C]95[/C][/ROW]
[ROW][C]4[/C][C]460.583333333333[/C][C]6.38831793671903[/C][C]115[/C][/ROW]
[ROW][C]5[/C][C]466.083333333333[/C][C]5.77547059606926[/C][C]113[/C][/ROW]
[ROW][C]6[/C][C]435.75[/C][C]17.1099386322687[/C][C]107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5964&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5964&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
1364.5833333333338.85702939460917
2393.41666666666714.189998611911950
3426.16666666666710.477971119824695
4460.5833333333336.38831793671903115
5466.0833333333335.77547059606926113
6435.7517.1099386322687107






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha26.2393028001993
beta-0.0371623772413206
S.D.0.0535672770188398
T-STAT-0.693751471224688
p-value0.526019242874499

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 26.2393028001993 \tabularnewline
beta & -0.0371623772413206 \tabularnewline
S.D. & 0.0535672770188398 \tabularnewline
T-STAT & -0.693751471224688 \tabularnewline
p-value & 0.526019242874499 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5964&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]26.2393028001993[/C][/ROW]
[ROW][C]beta[/C][C]-0.0371623772413206[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0535672770188398[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.693751471224688[/C][/ROW]
[ROW][C]p-value[/C][C]0.526019242874499[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5964&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5964&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)
alpha26.2393028001993
beta-0.0371623772413206
S.D.0.0535672770188398
T-STAT-0.693751471224688
p-value0.526019242874499






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha13.3721854932670
beta-1.83566611186076
S.D.2.07369033757024
T-STAT-0.88521708309237
p-value0.426046032710367
Lambda2.83566611186076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 13.3721854932670 \tabularnewline
beta & -1.83566611186076 \tabularnewline
S.D. & 2.07369033757024 \tabularnewline
T-STAT & -0.88521708309237 \tabularnewline
p-value & 0.426046032710367 \tabularnewline
Lambda & 2.83566611186076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5964&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.3721854932670[/C][/ROW]
[ROW][C]beta[/C][C]-1.83566611186076[/C][/ROW]
[ROW][C]S.D.[/C][C]2.07369033757024[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.88521708309237[/C][/ROW]
[ROW][C]p-value[/C][C]0.426046032710367[/C][/ROW]
[ROW][C]Lambda[/C][C]2.83566611186076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5964&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5964&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)
alpha13.3721854932670
beta-1.83566611186076
S.D.2.07369033757024
T-STAT-0.88521708309237
p-value0.426046032710367
Lambda2.83566611186076


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')