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Description of Statistical Computation

Author's title

evolutie prijzen middagmaal spreidings- en gemiddeldegrafieken(Van Puymbroe...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 19 May 2008 08:49:30 -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/19/t12112086387uurjqydpmtahrs.htm/, Retrieved Tue, 14 May 2024 02:05:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12882, Retrieved Tue, 14 May 2024 02:05:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210

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] [evolutie prijzen ...] [2008-05-19 14:49:30] [e120e668935a0d64689fc62dff0df290] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.9
2.9
2.9
2.9
2.9
2.9
2.9
2.9
2.95
2.96
2.96
2.96
2.96
2.96
2.96
2.96
2.96
2.96
2.96
2.96
3.04
3.04
3.04
3.04
3.04
3.04
3.04
3.04
3.04
3.03
3.03
3.03
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.15
3.26
3.26
3.27
3.27
3.27
3.27
3.27
3.27
3.27
3.27
3.27
3.27
3.32
3.32
3.32
3.32
3.32
3.32
3.32
3.32
3.32
3.32
3.32
3.33
3.41
3.42
3.42
3.42

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12882&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12882&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12882&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12.919166666666670.02843120351538670.06
22.986666666666670.03938927711338650.08
33.074166666666670.05615859576937330.12
43.188333333333330.05670230608318780.12
53.286666666666670.02461829819586650.0499999999999998
63.353333333333330.04754583115906240.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.91916666666667 & 0.0284312035153867 & 0.06 \tabularnewline
2 & 2.98666666666667 & 0.0393892771133865 & 0.08 \tabularnewline
3 & 3.07416666666667 & 0.0561585957693733 & 0.12 \tabularnewline
4 & 3.18833333333333 & 0.0567023060831878 & 0.12 \tabularnewline
5 & 3.28666666666667 & 0.0246182981958665 & 0.0499999999999998 \tabularnewline
6 & 3.35333333333333 & 0.0475458311590624 & 0.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12882&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]2.91916666666667[/C][C]0.0284312035153867[/C][C]0.06[/C][/ROW]
[ROW][C]2[/C][C]2.98666666666667[/C][C]0.0393892771133865[/C][C]0.08[/C][/ROW]
[ROW][C]3[/C][C]3.07416666666667[/C][C]0.0561585957693733[/C][C]0.12[/C][/ROW]
[ROW][C]4[/C][C]3.18833333333333[/C][C]0.0567023060831878[/C][C]0.12[/C][/ROW]
[ROW][C]5[/C][C]3.28666666666667[/C][C]0.0246182981958665[/C][C]0.0499999999999998[/C][/ROW]
[ROW][C]6[/C][C]3.35333333333333[/C][C]0.0475458311590624[/C][C]0.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12882&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12882&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
12.919166666666670.02843120351538670.06
22.986666666666670.03938927711338650.08
33.074166666666670.05615859576937330.12
43.188333333333330.05670230608318780.12
53.286666666666670.02461829819586650.0499999999999998
63.353333333333330.04754583115906240.1






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.00315107927322844
beta0.0124380524340395
S.D.0.0396688216207165
T-STAT0.313547313125729
p-value0.769534880974799

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.00315107927322844 \tabularnewline
beta & 0.0124380524340395 \tabularnewline
S.D. & 0.0396688216207165 \tabularnewline
T-STAT & 0.313547313125729 \tabularnewline
p-value & 0.769534880974799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12882&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.00315107927322844[/C][/ROW]
[ROW][C]beta[/C][C]0.0124380524340395[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0396688216207165[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.313547313125729[/C][/ROW]
[ROW][C]p-value[/C][C]0.769534880974799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12882&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12882&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)
alpha0.00315107927322844
beta0.0124380524340395
S.D.0.0396688216207165
T-STAT0.313547313125729
p-value0.769534880974799






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.21898929916109
beta0.879048563537551
S.D.3.19713495426943
T-STAT0.274948845172668
p-value0.796972896027955
Lambda0.120951436462449

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.21898929916109 \tabularnewline
beta & 0.879048563537551 \tabularnewline
S.D. & 3.19713495426943 \tabularnewline
T-STAT & 0.274948845172668 \tabularnewline
p-value & 0.796972896027955 \tabularnewline
Lambda & 0.120951436462449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12882&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.21898929916109[/C][/ROW]
[ROW][C]beta[/C][C]0.879048563537551[/C][/ROW]
[ROW][C]S.D.[/C][C]3.19713495426943[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.274948845172668[/C][/ROW]
[ROW][C]p-value[/C][C]0.796972896027955[/C][/ROW]
[ROW][C]Lambda[/C][C]0.120951436462449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12882&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12882&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-4.21898929916109
beta0.879048563537551
S.D.3.19713495426943
T-STAT0.274948845172668
p-value0.796972896027955
Lambda0.120951436462449


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')