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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 computationFri, 19 Dec 2008 14:48:16 -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/19/t12297233741n4egaup5bkz756.htm/, Retrieved Thu, 16 May 2024 02:48:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35267, Retrieved Thu, 16 May 2024 02:48:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
F    D  [Multiple Regression] [Seatbelt law: q1] [2008-11-24 23:03:38] [8d78428855b119373cac369316c08983]
- R PD    [Multiple Regression] [Multiple lineair ...] [2008-12-19 20:37:22] [8d78428855b119373cac369316c08983]
- RMPD      [Standard Deviation-Mean Plot] [smp] [2008-12-19 21:43:48] [8d78428855b119373cac369316c08983]
-    D          [Standard Deviation-Mean Plot] [smp] [2008-12-19 21:48:16] [d6e9f26c3644bfc30f06303d9993b878] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572

Tables (Output of Computation)





Summary of computational 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 computational 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=35267&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]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=35267&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35267&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
123735.256529.3185378094320890
222458.83333333335033.6520780070115936
323118.57012.6951828289823808
423009.83333333336104.5245192447721757
524156.256153.2285409590219196

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 23735.25 & 6529.31853780943 & 20890 \tabularnewline
2 & 22458.8333333333 & 5033.65207800701 & 15936 \tabularnewline
3 & 23118.5 & 7012.69518282898 & 23808 \tabularnewline
4 & 23009.8333333333 & 6104.52451924477 & 21757 \tabularnewline
5 & 24156.25 & 6153.22854095902 & 19196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35267&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]23735.25[/C][C]6529.31853780943[/C][C]20890[/C][/ROW]
[ROW][C]2[/C][C]22458.8333333333[/C][C]5033.65207800701[/C][C]15936[/C][/ROW]
[ROW][C]3[/C][C]23118.5[/C][C]7012.69518282898[/C][C]23808[/C][/ROW]
[ROW][C]4[/C][C]23009.8333333333[/C][C]6104.52451924477[/C][C]21757[/C][/ROW]
[ROW][C]5[/C][C]24156.25[/C][C]6153.22854095902[/C][C]19196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35267&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35267&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
123735.256529.3185378094320890
222458.83333333335033.6520780070115936
323118.57012.6951828289823808
423009.83333333336104.5245192447721757
524156.256153.2285409590219196






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-6684.64818029097
beta0.551660330592475
S.D.0.55306436915282
T-STAT0.99746134692695
p-value0.392053276557717

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -6684.64818029097 \tabularnewline
beta & 0.551660330592475 \tabularnewline
S.D. & 0.55306436915282 \tabularnewline
T-STAT & 0.99746134692695 \tabularnewline
p-value & 0.392053276557717 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35267&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6684.64818029097[/C][/ROW]
[ROW][C]beta[/C][C]0.551660330592475[/C][/ROW]
[ROW][C]S.D.[/C][C]0.55306436915282[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.99746134692695[/C][/ROW]
[ROW][C]p-value[/C][C]0.392053276557717[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35267&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35267&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)
alpha-6684.64818029097
beta0.551660330592475
S.D.0.55306436915282
T-STAT0.99746134692695
p-value0.392053276557717






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-14.9017447567912
beta2.34918765683547
S.D.2.11680501065051
T-STAT1.10977990179339
p-value0.348051227903868
Lambda-1.34918765683547

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -14.9017447567912 \tabularnewline
beta & 2.34918765683547 \tabularnewline
S.D. & 2.11680501065051 \tabularnewline
T-STAT & 1.10977990179339 \tabularnewline
p-value & 0.348051227903868 \tabularnewline
Lambda & -1.34918765683547 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35267&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-14.9017447567912[/C][/ROW]
[ROW][C]beta[/C][C]2.34918765683547[/C][/ROW]
[ROW][C]S.D.[/C][C]2.11680501065051[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.10977990179339[/C][/ROW]
[ROW][C]p-value[/C][C]0.348051227903868[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.34918765683547[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35267&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35267&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-14.9017447567912
beta2.34918765683547
S.D.2.11680501065051
T-STAT1.10977990179339
p-value0.348051227903868
Lambda-1.34918765683547


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')