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Description of Statistical Computation

Author's title

De spreidings- en gemiddeldegrafieken van de gemiddelde consumptieprijs van...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 04 Dec 2010 17:45:24 +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/2010/Dec/04/t1291484927nlh9zbyy3b4e4sj.htm/, Retrieved Sat, 04 May 2024 21:08:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105236, Retrieved Sat, 04 May 2024 21:08:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83 - Kristina Henderickx
Estimated Impact108

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] [De spreidings- en...] [2010-12-04 17:45:24] [96acfd0c13fab69dd0825b64c3919859] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.65
0.65
0.65
0.65
0.65
0.65
0.66
0.66
0.66
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.66
0.67
0.66
0.67
0.66
0.66
0.66
0.66
0.71
0.74
0.75
0.75
0.75
0.75
0.7
0.69
0.69
0.68
0.68
0.68
0.67
0.66
0.66
0.67
0.67
0.67
0.67
0.68
0.68
0.67
0.67
0.67
0.67
0.67
0.69
0.69
0.69
0.69
0.69
0.69
0.7
0.69
0.68
0.7
0.7
0.71
0.69
0.7
0.7
0.71
0.71
0.71
0.71
0.7
0.7
0.71
0.71
0.71
0.71
0.7
0.69
0.7
0.7
0.7
0.71
0.7
0.7
0.69

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105236&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]4 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=105236&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105236&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 time4 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.65250.004522670168666460.01
20.6583333333333330.007177405625652740.02
30.7141666666666670.03117642854737690.07
40.670.006030226891555280.02
50.68750.00965307299163420.0299999999999999
60.7041666666666670.006685579234215220.02
70.7016666666666670.007177405625652740.02

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.6525 & 0.00452267016866646 & 0.01 \tabularnewline
2 & 0.658333333333333 & 0.00717740562565274 & 0.02 \tabularnewline
3 & 0.714166666666667 & 0.0311764285473769 & 0.07 \tabularnewline
4 & 0.67 & 0.00603022689155528 & 0.02 \tabularnewline
5 & 0.6875 & 0.0096530729916342 & 0.0299999999999999 \tabularnewline
6 & 0.704166666666667 & 0.00668557923421522 & 0.02 \tabularnewline
7 & 0.701666666666667 & 0.00717740562565274 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105236&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]0.6525[/C][C]0.00452267016866646[/C][C]0.01[/C][/ROW]
[ROW][C]2[/C][C]0.658333333333333[/C][C]0.00717740562565274[/C][C]0.02[/C][/ROW]
[ROW][C]3[/C][C]0.714166666666667[/C][C]0.0311764285473769[/C][C]0.07[/C][/ROW]
[ROW][C]4[/C][C]0.67[/C][C]0.00603022689155528[/C][C]0.02[/C][/ROW]
[ROW][C]5[/C][C]0.6875[/C][C]0.0096530729916342[/C][C]0.0299999999999999[/C][/ROW]
[ROW][C]6[/C][C]0.704166666666667[/C][C]0.00668557923421522[/C][C]0.02[/C][/ROW]
[ROW][C]7[/C][C]0.701666666666667[/C][C]0.00717740562565274[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105236&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105236&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
10.65250.004522670168666460.01
20.6583333333333330.007177405625652740.02
30.7141666666666670.03117642854737690.07
40.670.006030226891555280.02
50.68750.00965307299163420.0299999999999999
60.7041666666666670.006685579234215220.02
70.7016666666666670.007177405625652740.02






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.150727268366270
beta0.235471006122238
S.D.0.136928691874316
T-STAT1.71966154718232
p-value0.146125785594172

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.150727268366270 \tabularnewline
beta & 0.235471006122238 \tabularnewline
S.D. & 0.136928691874316 \tabularnewline
T-STAT & 1.71966154718232 \tabularnewline
p-value & 0.146125785594172 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105236&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.150727268366270[/C][/ROW]
[ROW][C]beta[/C][C]0.235471006122238[/C][/ROW]
[ROW][C]S.D.[/C][C]0.136928691874316[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.71966154718232[/C][/ROW]
[ROW][C]p-value[/C][C]0.146125785594172[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105236&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105236&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-0.150727268366270
beta0.235471006122238
S.D.0.136928691874316
T-STAT1.71966154718232
p-value0.146125785594172






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.285213393151806
beta11.8351207467703
S.D.5.85309218331139
T-STAT2.0220287629358
p-value0.0991134826911367
Lambda-10.8351207467703

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.285213393151806 \tabularnewline
beta & 11.8351207467703 \tabularnewline
S.D. & 5.85309218331139 \tabularnewline
T-STAT & 2.0220287629358 \tabularnewline
p-value & 0.0991134826911367 \tabularnewline
Lambda & -10.8351207467703 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105236&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.285213393151806[/C][/ROW]
[ROW][C]beta[/C][C]11.8351207467703[/C][/ROW]
[ROW][C]S.D.[/C][C]5.85309218331139[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.0220287629358[/C][/ROW]
[ROW][C]p-value[/C][C]0.0991134826911367[/C][/ROW]
[ROW][C]Lambda[/C][C]-10.8351207467703[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105236&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105236&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-0.285213393151806
beta11.8351207467703
S.D.5.85309218331139
T-STAT2.0220287629358
p-value0.0991134826911367
Lambda-10.8351207467703


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')