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Description of Statistical Computation

Author's title

Standard Deviation - Mean Plot - Gemiddelde bioscoopprijs (Jeroen Callebaut...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 20 Dec 2008 06:50:00 -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/20/t1229781044l6cag6161dl2g8k.htm/, Retrieved Sun, 19 May 2024 12:15:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35363, Retrieved Sun, 19 May 2024 12:15:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact215

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] [Standard Deviatio...] [2008-12-20 13:50:00] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5.6
5.6
5.6
5.6
5.6
5.67
5.67
5.67
5.67
5.67
5.67
5.67
5.67
5.67
5.82
5.82
5.95
5.95
5.95
5.95
5.95
5.95
6.02
6.02
6.05
6.05
6.05
6.12
6.12
6.12
6.12
6.12
6.12
6.12
6.12
6.17
6.17
6.17
6.17
6.17
6.28
6.27
6.28
6.28
6.27
6.27
6.28
6.59
6.59
6.59
6.59
6.59
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.63
6.79
6.79
6.79

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35363&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35363&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35363&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
15.640833333333330.03604500553811070.0700000000000003
25.893333333333330.1213060242327290.350
36.106666666666670.03700941731096260.12
46.266666666666670.1138845774005280.42
56.616666666666670.01969463855669330.04
66.670.07236272269866330.16

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5.64083333333333 & 0.0360450055381107 & 0.0700000000000003 \tabularnewline
2 & 5.89333333333333 & 0.121306024232729 & 0.350 \tabularnewline
3 & 6.10666666666667 & 0.0370094173109626 & 0.12 \tabularnewline
4 & 6.26666666666667 & 0.113884577400528 & 0.42 \tabularnewline
5 & 6.61666666666667 & 0.0196946385566933 & 0.04 \tabularnewline
6 & 6.67 & 0.0723627226986633 & 0.16 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35363&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]5.64083333333333[/C][C]0.0360450055381107[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]2[/C][C]5.89333333333333[/C][C]0.121306024232729[/C][C]0.350[/C][/ROW]
[ROW][C]3[/C][C]6.10666666666667[/C][C]0.0370094173109626[/C][C]0.12[/C][/ROW]
[ROW][C]4[/C][C]6.26666666666667[/C][C]0.113884577400528[/C][C]0.42[/C][/ROW]
[ROW][C]5[/C][C]6.61666666666667[/C][C]0.0196946385566933[/C][C]0.04[/C][/ROW]
[ROW][C]6[/C][C]6.67[/C][C]0.0723627226986633[/C][C]0.16[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35363&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35363&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
15.640833333333330.03604500553811070.0700000000000003
25.893333333333330.1213060242327290.350
36.106666666666670.03700941731096260.12
46.266666666666670.1138845774005280.42
56.616666666666670.01969463855669330.04
66.670.07236272269866330.16






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.147494562136632
beta-0.0130306720251501
S.D.0.0529491734173405
T-STAT-0.246097742120422
p-value0.817719117603873

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.147494562136632 \tabularnewline
beta & -0.0130306720251501 \tabularnewline
S.D. & 0.0529491734173405 \tabularnewline
T-STAT & -0.246097742120422 \tabularnewline
p-value & 0.817719117603873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35363&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.147494562136632[/C][/ROW]
[ROW][C]beta[/C][C]-0.0130306720251501[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0529491734173405[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.246097742120422[/C][/ROW]
[ROW][C]p-value[/C][C]0.817719117603873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35363&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35363&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)
alpha0.147494562136632
beta-0.0130306720251501
S.D.0.0529491734173405
T-STAT-0.246097742120422
p-value0.817719117603873






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.0777300040152217
beta-1.55350691318615
S.D.5.47824673200642
T-STAT-0.283577390574589
p-value0.790806483568595
Lambda2.55350691318615

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.0777300040152217 \tabularnewline
beta & -1.55350691318615 \tabularnewline
S.D. & 5.47824673200642 \tabularnewline
T-STAT & -0.283577390574589 \tabularnewline
p-value & 0.790806483568595 \tabularnewline
Lambda & 2.55350691318615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35363&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0777300040152217[/C][/ROW]
[ROW][C]beta[/C][C]-1.55350691318615[/C][/ROW]
[ROW][C]S.D.[/C][C]5.47824673200642[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.283577390574589[/C][/ROW]
[ROW][C]p-value[/C][C]0.790806483568595[/C][/ROW]
[ROW][C]Lambda[/C][C]2.55350691318615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35363&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35363&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-0.0777300040152217
beta-1.55350691318615
S.D.5.47824673200642
T-STAT-0.283577390574589
p-value0.790806483568595
Lambda2.55350691318615


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')