FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 21 Dec 2008 11:58:58 -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/2008/Dec/21/t1229886006w7y63ufn2qtdhs1.htm/, Retrieved Fri, 17 May 2024 01:41:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35756, Retrieved Fri, 17 May 2024 01:41:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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] [fdsfq] [2008-12-21 18:58:58] [7a2afff08a618fdf6611a1bb6e1c3da4] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
485
464
460
467
460
448
443
436
431
484
510
513
503
471
471
476
475
470
461
455
456
517
525
523
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
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35756&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35756&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35756&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1466.7526.761998158854882
2483.58333333333326.081893173524670
3527.529.598832900824179
4565.58333333333326.137602078695876
5595.91666666666721.919100567700562
6596.08333333333319.430333985494953
7545.91666666666725.238708846579889

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 466.75 & 26.7619981588548 & 82 \tabularnewline
2 & 483.583333333333 & 26.0818931735246 & 70 \tabularnewline
3 & 527.5 & 29.5988329008241 & 79 \tabularnewline
4 & 565.583333333333 & 26.1376020786958 & 76 \tabularnewline
5 & 595.916666666667 & 21.9191005677005 & 62 \tabularnewline
6 & 596.083333333333 & 19.4303339854949 & 53 \tabularnewline
7 & 545.916666666667 & 25.2387088465798 & 89 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35756&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]466.75[/C][C]26.7619981588548[/C][C]82[/C][/ROW]
[ROW][C]2[/C][C]483.583333333333[/C][C]26.0818931735246[/C][C]70[/C][/ROW]
[ROW][C]3[/C][C]527.5[/C][C]29.5988329008241[/C][C]79[/C][/ROW]
[ROW][C]4[/C][C]565.583333333333[/C][C]26.1376020786958[/C][C]76[/C][/ROW]
[ROW][C]5[/C][C]595.916666666667[/C][C]21.9191005677005[/C][C]62[/C][/ROW]
[ROW][C]6[/C][C]596.083333333333[/C][C]19.4303339854949[/C][C]53[/C][/ROW]
[ROW][C]7[/C][C]545.916666666667[/C][C]25.2387088465798[/C][C]89[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35756&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35756&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
1466.7526.761998158854882
2483.58333333333326.081893173524670
3527.529.598832900824179
4565.58333333333326.137602078695876
5595.91666666666721.919100567700562
6596.08333333333319.430333985494953
7545.91666666666725.238708846579889






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha49.2215042964872
beta-0.0447942684318765
S.D.0.0213936294185567
T-STAT-2.09381342246782
p-value0.0904607970523805

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 49.2215042964872 \tabularnewline
beta & -0.0447942684318765 \tabularnewline
S.D. & 0.0213936294185567 \tabularnewline
T-STAT & -2.09381342246782 \tabularnewline
p-value & 0.0904607970523805 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35756&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]49.2215042964872[/C][/ROW]
[ROW][C]beta[/C][C]-0.0447942684318765[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0213936294185567[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.09381342246782[/C][/ROW]
[ROW][C]p-value[/C][C]0.0904607970523805[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35756&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35756&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)
alpha49.2215042964872
beta-0.0447942684318765
S.D.0.0213936294185567
T-STAT-2.09381342246782
p-value0.0904607970523805






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha9.36604618977804
beta-0.978745097931178
S.D.0.480466828391814
T-STAT-2.03707111520511
p-value0.097230941049461
Lambda1.97874509793118

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.36604618977804 \tabularnewline
beta & -0.978745097931178 \tabularnewline
S.D. & 0.480466828391814 \tabularnewline
T-STAT & -2.03707111520511 \tabularnewline
p-value & 0.097230941049461 \tabularnewline
Lambda & 1.97874509793118 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35756&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.36604618977804[/C][/ROW]
[ROW][C]beta[/C][C]-0.978745097931178[/C][/ROW]
[ROW][C]S.D.[/C][C]0.480466828391814[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.03707111520511[/C][/ROW]
[ROW][C]p-value[/C][C]0.097230941049461[/C][/ROW]
[ROW][C]Lambda[/C][C]1.97874509793118[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35756&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35756&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)
alpha9.36604618977804
beta-0.978745097931178
S.D.0.480466828391814
T-STAT-2.03707111520511
p-value0.097230941049461
Lambda1.97874509793118


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')