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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, 07 May 2012 07:26:19 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/07/t1336389999ye622o1lcsutsrg.htm/, Retrieved Fri, 03 May 2024 03:53:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166300, Retrieved Fri, 03 May 2024 03:53:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variability] [OPG8 OEF3] [2012-04-29 13:25:40] [aedd9af56bfe2946a9f9da3d899aa64c]
- RMPD    [Standard Deviation-Mean Plot] [OPG8OEF3 juiste ] [2012-05-07 11:26:19] [2d897010b3abf24abba169db0d9c5a05] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
67.22
67.31
67.14
67.22
67.17
67.27
67.27
67.27
67.48
67.38
67.22
67.2
67.2
67.19
67.32
67.61
67.85
67.74
67.74
67.61
67.85
67.89
67.97
67.94
67.94
68.07
67.85
67.84
67.89
67.86
67.86
67.89
67.7
68.05
68.18
68.19
68.19
68.27
68.22
68.14
68.36
68.34
68.34
68.24
68.14
68.23
68.09
68.03
68.03
67.89
67.63
67.61
67.41
67.29
67.29
67.49
67.68
68.05
67.7
67.86

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166300&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166300&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166300&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
167.26250.09362643371884410.340000000000003
267.65916666666670.2805014449268670.780000000000001
367.94333333333330.1484669129551230.489999999999995
468.21583333333330.1035249933225030.329999999999998
567.66083333333330.2615498677754070.759999999999991

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 67.2625 & 0.0936264337188441 & 0.340000000000003 \tabularnewline
2 & 67.6591666666667 & 0.280501444926867 & 0.780000000000001 \tabularnewline
3 & 67.9433333333333 & 0.148466912955123 & 0.489999999999995 \tabularnewline
4 & 68.2158333333333 & 0.103524993322503 & 0.329999999999998 \tabularnewline
5 & 67.6608333333333 & 0.261549867775407 & 0.759999999999991 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166300&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]67.2625[/C][C]0.0936264337188441[/C][C]0.340000000000003[/C][/ROW]
[ROW][C]2[/C][C]67.6591666666667[/C][C]0.280501444926867[/C][C]0.780000000000001[/C][/ROW]
[ROW][C]3[/C][C]67.9433333333333[/C][C]0.148466912955123[/C][C]0.489999999999995[/C][/ROW]
[ROW][C]4[/C][C]68.2158333333333[/C][C]0.103524993322503[/C][C]0.329999999999998[/C][/ROW]
[ROW][C]5[/C][C]67.6608333333333[/C][C]0.261549867775407[/C][C]0.759999999999991[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166300&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166300&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
167.26250.09362643371884410.340000000000003
267.65916666666670.2805014449268670.780000000000001
367.94333333333330.1484669129551230.489999999999995
468.21583333333330.1035249933225030.329999999999998
567.66083333333330.2615498677754070.759999999999991






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.31505265261055
beta-0.0315508679977977
S.D.0.141477977316764
T-STAT-0.22300904067321
p-value0.837850059915117

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.31505265261055 \tabularnewline
beta & -0.0315508679977977 \tabularnewline
S.D. & 0.141477977316764 \tabularnewline
T-STAT & -0.22300904067321 \tabularnewline
p-value & 0.837850059915117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166300&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.31505265261055[/C][/ROW]
[ROW][C]beta[/C][C]-0.0315508679977977[/C][/ROW]
[ROW][C]S.D.[/C][C]0.141477977316764[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.22300904067321[/C][/ROW]
[ROW][C]p-value[/C][C]0.837850059915117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166300&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166300&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)
alpha2.31505265261055
beta-0.0315508679977977
S.D.0.141477977316764
T-STAT-0.22300904067321
p-value0.837850059915117






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha25.8338832508486
beta-6.56225954024139
S.D.55.7912078727675
T-STAT-0.11762175063868
p-value0.913800369199763
Lambda7.56225954024139

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 25.8338832508486 \tabularnewline
beta & -6.56225954024139 \tabularnewline
S.D. & 55.7912078727675 \tabularnewline
T-STAT & -0.11762175063868 \tabularnewline
p-value & 0.913800369199763 \tabularnewline
Lambda & 7.56225954024139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166300&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]25.8338832508486[/C][/ROW]
[ROW][C]beta[/C][C]-6.56225954024139[/C][/ROW]
[ROW][C]S.D.[/C][C]55.7912078727675[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.11762175063868[/C][/ROW]
[ROW][C]p-value[/C][C]0.913800369199763[/C][/ROW]
[ROW][C]Lambda[/C][C]7.56225954024139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166300&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166300&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)
alpha25.8338832508486
beta-6.56225954024139
S.D.55.7912078727675
T-STAT-0.11762175063868
p-value0.913800369199763
Lambda7.56225954024139


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')