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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 computationSun, 16 Jan 2011 15:39:13 +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/2011/Jan/16/t1295192276wds939q62t3kglk.htm/, Retrieved Sat, 18 May 2024 06:16:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=117432, Retrieved Sat, 18 May 2024 06:16:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact118

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [] [oef 8.3.3] [1970-01-01 00:00:00] [04d4ebd708b081bb203cd3af96bd9a4a]
- RMPD  [Standard Deviation-Mean Plot] [oef 8.3.3 ] [2010-12-07 21:27:00] [04d4ebd708b081bb203cd3af96bd9a4a]
-   PD      [Standard Deviation-Mean Plot] [Verbetering opgav...] [2011-01-16 15:39:13] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.02
101.15
101.51
101.75
101.8
101.8
101.8
101.82
101.99
102.25
102.34
102.35
102.35
102.39
102.49
102.67
102.68
102.7
102.71
102.72
102.83
102.92
103.04
103.08
103.09
103.11
103.18
103.18
103.22
103.25
103.25
103.25
103.47
103.57
103.66
103.7
103.7
103.75
103.85
104.02
104.13
104.17
104.18
104.2
104.5
104.78
104.88
104.89
104.9
104.95
105.24
105.35
105.44
105.46
105.47
105.48
105.75
106.1
106.19
106.23
106.24
106.25
106.35
106.48
106.52
106.55
106.55
106.56
106.89
107.09
107.24
107.28
107.3
107.31
107.47
107.35
107.31
107.32
107.32
107.34
107.53
107.72
107.75
107.79
107.81
107.9
107.8
107.86
107.8
107.74
107.75
107.83
107.8
107.81
107.86
107.83

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=117432&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=117432&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117432&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
1101.7983333333330.4210988511314671.33000000000000
2102.7150.2310253823126980.730000000000004
3103.32750.2143117949496590.61
4104.2541666666670.4203128344315441.19000000000000
5105.5466666666670.4435873047886921.33000000000000
6106.6666666666670.3674069661667831.04000000000001
7107.4591666666670.1911428943502920.490000000000009
8107.8158333333330.04501683186892780.160000000000011

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 101.798333333333 & 0.421098851131467 & 1.33000000000000 \tabularnewline
2 & 102.715 & 0.231025382312698 & 0.730000000000004 \tabularnewline
3 & 103.3275 & 0.214311794949659 & 0.61 \tabularnewline
4 & 104.254166666667 & 0.420312834431544 & 1.19000000000000 \tabularnewline
5 & 105.546666666667 & 0.443587304788692 & 1.33000000000000 \tabularnewline
6 & 106.666666666667 & 0.367406966166783 & 1.04000000000001 \tabularnewline
7 & 107.459166666667 & 0.191142894350292 & 0.490000000000009 \tabularnewline
8 & 107.815833333333 & 0.0450168318689278 & 0.160000000000011 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117432&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]101.798333333333[/C][C]0.421098851131467[/C][C]1.33000000000000[/C][/ROW]
[ROW][C]2[/C][C]102.715[/C][C]0.231025382312698[/C][C]0.730000000000004[/C][/ROW]
[ROW][C]3[/C][C]103.3275[/C][C]0.214311794949659[/C][C]0.61[/C][/ROW]
[ROW][C]4[/C][C]104.254166666667[/C][C]0.420312834431544[/C][C]1.19000000000000[/C][/ROW]
[ROW][C]5[/C][C]105.546666666667[/C][C]0.443587304788692[/C][C]1.33000000000000[/C][/ROW]
[ROW][C]6[/C][C]106.666666666667[/C][C]0.367406966166783[/C][C]1.04000000000001[/C][/ROW]
[ROW][C]7[/C][C]107.459166666667[/C][C]0.191142894350292[/C][C]0.490000000000009[/C][/ROW]
[ROW][C]8[/C][C]107.815833333333[/C][C]0.0450168318689278[/C][C]0.160000000000011[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117432&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117432&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
1101.7983333333330.4210988511314671.33000000000000
2102.7150.2310253823126980.730000000000004
3103.32750.2143117949496590.61
4104.2541666666670.4203128344315441.19000000000000
5105.5466666666670.4435873047886921.33000000000000
6106.6666666666670.3674069661667831.04000000000001
7107.4591666666670.1911428943502920.490000000000009
8107.8158333333330.04501683186892780.160000000000011






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.14491119230369
beta-0.0271865647782782
S.D.0.0232422317543569
T-STAT-1.16970543386747
p-value0.286477414090695

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.14491119230369 \tabularnewline
beta & -0.0271865647782782 \tabularnewline
S.D. & 0.0232422317543569 \tabularnewline
T-STAT & -1.16970543386747 \tabularnewline
p-value & 0.286477414090695 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117432&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.14491119230369[/C][/ROW]
[ROW][C]beta[/C][C]-0.0271865647782782[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0232422317543569[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.16970543386747[/C][/ROW]
[ROW][C]p-value[/C][C]0.286477414090695[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117432&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117432&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)
alpha3.14491119230369
beta-0.0271865647782782
S.D.0.0232422317543569
T-STAT-1.16970543386747
p-value0.286477414090695






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha81.8787046169062
beta-17.8997183506524
S.D.12.4070435225108
T-STAT-1.44270617880689
p-value0.19920211950333
Lambda18.8997183506524

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 81.8787046169062 \tabularnewline
beta & -17.8997183506524 \tabularnewline
S.D. & 12.4070435225108 \tabularnewline
T-STAT & -1.44270617880689 \tabularnewline
p-value & 0.19920211950333 \tabularnewline
Lambda & 18.8997183506524 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117432&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]81.8787046169062[/C][/ROW]
[ROW][C]beta[/C][C]-17.8997183506524[/C][/ROW]
[ROW][C]S.D.[/C][C]12.4070435225108[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.44270617880689[/C][/ROW]
[ROW][C]p-value[/C][C]0.19920211950333[/C][/ROW]
[ROW][C]Lambda[/C][C]18.8997183506524[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117432&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117432&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)
alpha81.8787046169062
beta-17.8997183506524
S.D.12.4070435225108
T-STAT-1.44270617880689
p-value0.19920211950333
Lambda18.8997183506524


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')