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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 computationMon, 26 Nov 2007 07:38:34 -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/26/t1196087334odqvdwuiloymydu.htm/, Retrieved Thu, 02 May 2024 15:57:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6592, Retrieved Thu, 02 May 2024 15:57:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact203

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] [vraag 1-3] [2007-11-26 14:38:34] [c40c597932a04e0e43159741c7e63e4c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,6500
103,8700
103,9400
105,3200
105,5400
106,0800
106,2100
105,5300
105,5600
105,1400
105,9700
105,4500
106,2200
106,3100
107,3800
109,3100
110,8200
111,2200
110,6600
110,7600
110,6900
111,0800
110,9700
110,2400
112,5100
111,5200
112,1300
112,2300
112,9200
111,8900
111,9900
111,5100
112,3300
112,0400
112,0900
111,4100
112,6100
113,1400
113,6500
114,2600
114,4000
114,9300
114,8600
114,9500
116,1700
114,6000
114,6200
113,8200
115,0200
115,1800
115,5900
116,6000
117,0700
116,9600
116,6600
116,0700
116,0400
115,8100
116,2200
115,8500
116,4300
117,3900
119,1700
119,2400
120,0300

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6592&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]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=6592&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6592&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1105.1883333333330.8831434901772312.55999999999999
2109.6383333333331.894738328459467.35
3112.04750.4367883822963848.98
4114.3341666666670.9378162092991610.85
5116.0891666666670.6523448381636711.5300000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 105.188333333333 & 0.883143490177231 & 2.55999999999999 \tabularnewline
2 & 109.638333333333 & 1.89473832845946 & 7.35 \tabularnewline
3 & 112.0475 & 0.436788382296384 & 8.98 \tabularnewline
4 & 114.334166666667 & 0.93781620929916 & 10.85 \tabularnewline
5 & 116.089166666667 & 0.65234483816367 & 11.5300000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6592&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]105.188333333333[/C][C]0.883143490177231[/C][C]2.55999999999999[/C][/ROW]
[ROW][C]2[/C][C]109.638333333333[/C][C]1.89473832845946[/C][C]7.35[/C][/ROW]
[ROW][C]3[/C][C]112.0475[/C][C]0.436788382296384[/C][C]8.98[/C][/ROW]
[ROW][C]4[/C][C]114.334166666667[/C][C]0.93781620929916[/C][C]10.85[/C][/ROW]
[ROW][C]5[/C][C]116.089166666667[/C][C]0.65234483816367[/C][C]11.5300000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6592&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6592&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
1105.1883333333330.8831434901772312.55999999999999
2109.6383333333331.894738328459467.35
3112.04750.4367883822963848.98
4114.3341666666670.9378162092991610.85
5116.0891666666670.6523448381636711.5300000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.58586939767123
beta-0.0414940238202401
S.D.0.0717750429482823
T-STAT-0.578112141989782
p-value0.603727777449564

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.58586939767123 \tabularnewline
beta & -0.0414940238202401 \tabularnewline
S.D. & 0.0717750429482823 \tabularnewline
T-STAT & -0.578112141989782 \tabularnewline
p-value & 0.603727777449564 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6592&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.58586939767123[/C][/ROW]
[ROW][C]beta[/C][C]-0.0414940238202401[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0717750429482823[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.578112141989782[/C][/ROW]
[ROW][C]p-value[/C][C]0.603727777449564[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6592&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6592&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)
alpha5.58586939767123
beta-0.0414940238202401
S.D.0.0717750429482823
T-STAT-0.578112141989782
p-value0.603727777449564






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha21.3543091340711
beta-4.56502614102647
S.D.7.64013294235206
T-STAT-0.597506113502404
p-value0.592263979857774
Lambda5.56502614102647

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 21.3543091340711 \tabularnewline
beta & -4.56502614102647 \tabularnewline
S.D. & 7.64013294235206 \tabularnewline
T-STAT & -0.597506113502404 \tabularnewline
p-value & 0.592263979857774 \tabularnewline
Lambda & 5.56502614102647 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6592&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]21.3543091340711[/C][/ROW]
[ROW][C]beta[/C][C]-4.56502614102647[/C][/ROW]
[ROW][C]S.D.[/C][C]7.64013294235206[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.597506113502404[/C][/ROW]
[ROW][C]p-value[/C][C]0.592263979857774[/C][/ROW]
[ROW][C]Lambda[/C][C]5.56502614102647[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6592&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6592&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)
alpha21.3543091340711
beta-4.56502614102647
S.D.7.64013294235206
T-STAT-0.597506113502404
p-value0.592263979857774
Lambda5.56502614102647


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')