FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSun, 26 Dec 2010 13:27:22 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/26/t1293369891wx9sgkwrjxo69se.htm/, Retrieved Mon, 06 May 2024 12:13:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115599, Retrieved Mon, 06 May 2024 12:13:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [tijdreeks bevolki...] [2010-12-26 10:20:42] [efd13e24149aec704f3383e33c1e842a]
- RMPD    [Standard Deviation-Mean Plot] [tijdreeks werkloo...] [2010-12-26 13:27:22] [531024149246456e4f6d79ace2e85c12] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
332
369
384
373
378
426
423
397
422
409
430
412
396
470
491
504
484
474
508
492
452
457
457
471
451
476
493
514
522
490
484
506
501
462
465
454
464
427
482
460
473
465
422
415
413
420
363
376
380
384
346
410
389
407
393
346
348
353
364
305
307
312
312
286
344
324
336
327
302
299
311
315
264
278
278
287
279
300
324
354
354
360
363
385
412
370
389
395
417
404
377
456
478
468
437
432
441
449
386
396
394

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115599&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115599&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115599&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1396.2529.708049108249898
2471.33333333333329.9312343193325112
3484.83333333333323.59442666599471
4431.66666666666738.0103654124487119
5368.7530.6330926227889105
6314.58333333333316.149631762384158
7318.83333333333342.4474719952541121
8419.58333333333335.2380433192551108

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 396.25 & 29.7080491082498 & 98 \tabularnewline
2 & 471.333333333333 & 29.9312343193325 & 112 \tabularnewline
3 & 484.833333333333 & 23.594426665994 & 71 \tabularnewline
4 & 431.666666666667 & 38.0103654124487 & 119 \tabularnewline
5 & 368.75 & 30.6330926227889 & 105 \tabularnewline
6 & 314.583333333333 & 16.1496317623841 & 58 \tabularnewline
7 & 318.833333333333 & 42.4474719952541 & 121 \tabularnewline
8 & 419.583333333333 & 35.2380433192551 & 108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115599&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]396.25[/C][C]29.7080491082498[/C][C]98[/C][/ROW]
[ROW][C]2[/C][C]471.333333333333[/C][C]29.9312343193325[/C][C]112[/C][/ROW]
[ROW][C]3[/C][C]484.833333333333[/C][C]23.594426665994[/C][C]71[/C][/ROW]
[ROW][C]4[/C][C]431.666666666667[/C][C]38.0103654124487[/C][C]119[/C][/ROW]
[ROW][C]5[/C][C]368.75[/C][C]30.6330926227889[/C][C]105[/C][/ROW]
[ROW][C]6[/C][C]314.583333333333[/C][C]16.1496317623841[/C][C]58[/C][/ROW]
[ROW][C]7[/C][C]318.833333333333[/C][C]42.4474719952541[/C][C]121[/C][/ROW]
[ROW][C]8[/C][C]419.583333333333[/C][C]35.2380433192551[/C][C]108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115599&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115599&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
1396.2529.708049108249898
2471.33333333333329.9312343193325112
3484.83333333333323.59442666599471
4431.66666666666738.0103654124487119
5368.7530.6330926227889105
6314.58333333333316.149631762384158
7318.83333333333342.4474719952541121
8419.58333333333335.2380433192551108






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha31.3064401079615
beta-0.00147830693776482
S.D.0.0527079011987386
T-STAT-0.0280471599920241
p-value0.978534148704947

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 31.3064401079615 \tabularnewline
beta & -0.00147830693776482 \tabularnewline
S.D. & 0.0527079011987386 \tabularnewline
T-STAT & -0.0280471599920241 \tabularnewline
p-value & 0.978534148704947 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115599&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]31.3064401079615[/C][/ROW]
[ROW][C]beta[/C][C]-0.00147830693776482[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0527079011987386[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0280471599920241[/C][/ROW]
[ROW][C]p-value[/C][C]0.978534148704947[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115599&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115599&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)
alpha31.3064401079615
beta-0.00147830693776482
S.D.0.0527079011987386
T-STAT-0.0280471599920241
p-value0.978534148704947






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.89918917806796
beta0.248881110787628
S.D.0.749778936483308
T-STAT0.331939320614896
p-value0.751223840326119
Lambda0.751118889212372

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.89918917806796 \tabularnewline
beta & 0.248881110787628 \tabularnewline
S.D. & 0.749778936483308 \tabularnewline
T-STAT & 0.331939320614896 \tabularnewline
p-value & 0.751223840326119 \tabularnewline
Lambda & 0.751118889212372 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115599&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.89918917806796[/C][/ROW]
[ROW][C]beta[/C][C]0.248881110787628[/C][/ROW]
[ROW][C]S.D.[/C][C]0.749778936483308[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.331939320614896[/C][/ROW]
[ROW][C]p-value[/C][C]0.751223840326119[/C][/ROW]
[ROW][C]Lambda[/C][C]0.751118889212372[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115599&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115599&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)
alpha1.89918917806796
beta0.248881110787628
S.D.0.749778936483308
T-STAT0.331939320614896
p-value0.751223840326119
Lambda0.751118889212372


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')