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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 computationThu, 15 May 2008 10:10:34 -0600
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/May/15/t12108679251929l582cubasg0.htm/, Retrieved Tue, 14 May 2024 03:06:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12581, Retrieved Tue, 14 May 2024 03:06:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSreidings- en gemiddeldegrafieken - Blue Jeans (D) - Alexia Versluys
Estimated Impact252

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] [Sreidings- en gem...] [2008-05-15 16:10:34] [e8c1fcf34dff5578299591fe58b62c2d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
44,13
44,13
44,17
44,14
44,15
44,14
44,14
44,14
44,19
44,29
44,29
44,29
44,29
44,27
44,26
44,33
44,32
44,34
44,34
44,34
44,37
44,47
44,51
44,51
44,51
44,52
44,7
44,84
44,9
44,95
44,94
44,94
44,91
45,28
45,36
45,34
45,34
45,34
45,44
45,62
45,75
45,77
45,77
45,77
46,09
46,25
46,35
46,34
46,34
46,28
46,59
46,42
46,29
46,29
46,29
46,3
46,52
46,66
46,67
46,72
46,72
46,72
46,76
46,89
47,04
47,02
47,02
47,18
47,22
47,8
47,88
47,91

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12581&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12581&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12581&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
144.18333333333330.06651497894641710.159999999999997
244.36250.08729521490582620.25
344.93250.2832963433964830.850000000000001
445.81916666666670.3651514837168351.01000000000000
546.44750.1734738649427680.439999999999998
647.180.4434779896147351.19000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 44.1833333333333 & 0.0665149789464171 & 0.159999999999997 \tabularnewline
2 & 44.3625 & 0.0872952149058262 & 0.25 \tabularnewline
3 & 44.9325 & 0.283296343396483 & 0.850000000000001 \tabularnewline
4 & 45.8191666666667 & 0.365151483716835 & 1.01000000000000 \tabularnewline
5 & 46.4475 & 0.173473864942768 & 0.439999999999998 \tabularnewline
6 & 47.18 & 0.443477989614735 & 1.19000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12581&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]44.1833333333333[/C][C]0.0665149789464171[/C][C]0.159999999999997[/C][/ROW]
[ROW][C]2[/C][C]44.3625[/C][C]0.0872952149058262[/C][C]0.25[/C][/ROW]
[ROW][C]3[/C][C]44.9325[/C][C]0.283296343396483[/C][C]0.850000000000001[/C][/ROW]
[ROW][C]4[/C][C]45.8191666666667[/C][C]0.365151483716835[/C][C]1.01000000000000[/C][/ROW]
[ROW][C]5[/C][C]46.4475[/C][C]0.173473864942768[/C][C]0.439999999999998[/C][/ROW]
[ROW][C]6[/C][C]47.18[/C][C]0.443477989614735[/C][C]1.19000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12581&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12581&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
144.18333333333330.06651497894641710.159999999999997
244.36250.08729521490582620.25
344.93250.2832963433964830.850000000000001
445.81916666666670.3651514837168351.01000000000000
546.44750.1734738649427680.439999999999998
647.180.4434779896147351.19000000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4.17887852755054
beta0.09706872232601
S.D.0.0413936770881598
T-STAT2.34501327628551
p-value0.0789443744375278

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.17887852755054 \tabularnewline
beta & 0.09706872232601 \tabularnewline
S.D. & 0.0413936770881598 \tabularnewline
T-STAT & 2.34501327628551 \tabularnewline
p-value & 0.0789443744375278 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12581&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.17887852755054[/C][/ROW]
[ROW][C]beta[/C][C]0.09706872232601[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0413936770881598[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.34501327628551[/C][/ROW]
[ROW][C]p-value[/C][C]0.0789443744375278[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12581&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12581&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-4.17887852755054
beta0.09706872232601
S.D.0.0413936770881598
T-STAT2.34501327628551
p-value0.0789443744375278






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-89.0447474266978
beta22.8916943116455
S.D.9.37983302336245
T-STAT2.44052258229213
p-value0.0711683082940509
Lambda-21.8916943116455

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -89.0447474266978 \tabularnewline
beta & 22.8916943116455 \tabularnewline
S.D. & 9.37983302336245 \tabularnewline
T-STAT & 2.44052258229213 \tabularnewline
p-value & 0.0711683082940509 \tabularnewline
Lambda & -21.8916943116455 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12581&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-89.0447474266978[/C][/ROW]
[ROW][C]beta[/C][C]22.8916943116455[/C][/ROW]
[ROW][C]S.D.[/C][C]9.37983302336245[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.44052258229213[/C][/ROW]
[ROW][C]p-value[/C][C]0.0711683082940509[/C][/ROW]
[ROW][C]Lambda[/C][C]-21.8916943116455[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12581&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12581&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-89.0447474266978
beta22.8916943116455
S.D.9.37983302336245
T-STAT2.44052258229213
p-value0.0711683082940509
Lambda-21.8916943116455


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')