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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 computationSat, 17 May 2008 02:53:20 -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/17/t1211014666xoqy9856o25u6gz.htm/, Retrieved Tue, 14 May 2024 02:50:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12625, Retrieved Tue, 14 May 2024 02:50:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222

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] [Evelyne Van Haeve...] [2008-05-17 08:53:20] [c8f95257d399ca81c3dd1b8178a81b78] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13328
12873
14000
13477
14237
13674
13529
14058
12975
14326
14008
16193
14483
14011
15057
14884
15414
14440
14900
15074
14442
15307
14938
17193
15528
14765
15838
15723
16150
15486
15986
15983
15692
16490
15686
18897
16316
15636
17163
16534
16518
16375
16290
16352
15943
16362
16393
19051
16747
16320
17910
16961
17480
17049
16879
17473
16998
17307
17418
20169
17871
17226
19062
17804
19100
18522
18060
18869
18127
18871
18890
21263
19547
18450
20254
19240
20216
19420
19415
20018
18652
19978
19514
22148

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=12625&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=12625&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12625&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
113889.8333333333863.5795308253933320
215011.9166666667796.5601567573753182
316018.6666666667998.1870232242724132
416577.75856.9943380527933415
517392.5833333333967.1551025684783849
618638.751015.392546125524037
719737.6666666667944.7122056558563698

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 13889.8333333333 & 863.579530825393 & 3320 \tabularnewline
2 & 15011.9166666667 & 796.560156757375 & 3182 \tabularnewline
3 & 16018.6666666667 & 998.187023224272 & 4132 \tabularnewline
4 & 16577.75 & 856.994338052793 & 3415 \tabularnewline
5 & 17392.5833333333 & 967.155102568478 & 3849 \tabularnewline
6 & 18638.75 & 1015.39254612552 & 4037 \tabularnewline
7 & 19737.6666666667 & 944.712205655856 & 3698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12625&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]13889.8333333333[/C][C]863.579530825393[/C][C]3320[/C][/ROW]
[ROW][C]2[/C][C]15011.9166666667[/C][C]796.560156757375[/C][C]3182[/C][/ROW]
[ROW][C]3[/C][C]16018.6666666667[/C][C]998.187023224272[/C][C]4132[/C][/ROW]
[ROW][C]4[/C][C]16577.75[/C][C]856.994338052793[/C][C]3415[/C][/ROW]
[ROW][C]5[/C][C]17392.5833333333[/C][C]967.155102568478[/C][C]3849[/C][/ROW]
[ROW][C]6[/C][C]18638.75[/C][C]1015.39254612552[/C][C]4037[/C][/ROW]
[ROW][C]7[/C][C]19737.6666666667[/C][C]944.712205655856[/C][C]3698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12625&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12625&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
113889.8333333333863.5795308253933320
215011.9166666667796.5601567573753182
316018.6666666667998.1870232242724132
416577.75856.9943380527933415
517392.5833333333967.1551025684783849
618638.751015.392546125524037
719737.6666666667944.7122056558563698






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha503.538869408139
beta0.0248817200951620
S.D.0.0142817590912604
T-STAT1.74220275920970
p-value0.141941454850711

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 503.538869408139 \tabularnewline
beta & 0.0248817200951620 \tabularnewline
S.D. & 0.0142817590912604 \tabularnewline
T-STAT & 1.74220275920970 \tabularnewline
p-value & 0.141941454850711 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12625&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]503.538869408139[/C][/ROW]
[ROW][C]beta[/C][C]0.0248817200951620[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0142817590912604[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.74220275920970[/C][/ROW]
[ROW][C]p-value[/C][C]0.141941454850711[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12625&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12625&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)
alpha503.538869408139
beta0.0248817200951620
S.D.0.0142817590912604
T-STAT1.74220275920970
p-value0.141941454850711






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.28664021756408
beta0.466528309553468
S.D.0.260207560044202
T-STAT1.79290835928909
p-value0.132966115686222
Lambda0.533471690446532

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.28664021756408 \tabularnewline
beta & 0.466528309553468 \tabularnewline
S.D. & 0.260207560044202 \tabularnewline
T-STAT & 1.79290835928909 \tabularnewline
p-value & 0.132966115686222 \tabularnewline
Lambda & 0.533471690446532 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12625&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.28664021756408[/C][/ROW]
[ROW][C]beta[/C][C]0.466528309553468[/C][/ROW]
[ROW][C]S.D.[/C][C]0.260207560044202[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.79290835928909[/C][/ROW]
[ROW][C]p-value[/C][C]0.132966115686222[/C][/ROW]
[ROW][C]Lambda[/C][C]0.533471690446532[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12625&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12625&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)
alpha2.28664021756408
beta0.466528309553468
S.D.0.260207560044202
T-STAT1.79290835928909
p-value0.132966115686222
Lambda0.533471690446532


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')