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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 computationThu, 04 Jun 2009 11:57:57 -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/2009/Jun/04/t124413833736weathggg80ner.htm/, Retrieved Tue, 14 May 2024 14:35:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41733, Retrieved Tue, 14 May 2024 14:35:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsspreidings en gemiddeldegrafieken data aantal jonge werkzoekenden onder de 25 jaar in Vlaanderen
Estimated Impact128

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] [spreidings en gem...] [2009-06-04 17:57:57] [bddbb8640adbf7d76f1766fd0c9aa6ca] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
51772
48439
45716
43851
41622
45180
72550
77681
71177
63390
57386
56765
55772
53605
50338
47314
44596
47029
72490
78086
71058
63276
56918
55170
52980
50466
48553
46307
43796
45642
70765
75685
69220
62898
56011
54148
46626
46018
42408
42483
40113
41381
62348
63611
58389
46175
40555
37909
37866
34418
31736
29533
27604
30575
51345
52455
43367
37077
33016
33117
32279
30369
28983
27864
24591
29528
46549
47932
41584
37295
34666
36773
39591
39833

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=41733&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=41733&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41733&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
156294.083333333312367.820918219636059
25797110946.695117705633490
356372.583333333310766.120483496031889
447334.66666666678976.3048616731525702
536842.41666666678181.356460751424851
634867.757425.6567646480723341

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 56294.0833333333 & 12367.8209182196 & 36059 \tabularnewline
2 & 57971 & 10946.6951177056 & 33490 \tabularnewline
3 & 56372.5833333333 & 10766.1204834960 & 31889 \tabularnewline
4 & 47334.6666666667 & 8976.30486167315 & 25702 \tabularnewline
5 & 36842.4166666667 & 8181.3564607514 & 24851 \tabularnewline
6 & 34867.75 & 7425.65676464807 & 23341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41733&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]56294.0833333333[/C][C]12367.8209182196[/C][C]36059[/C][/ROW]
[ROW][C]2[/C][C]57971[/C][C]10946.6951177056[/C][C]33490[/C][/ROW]
[ROW][C]3[/C][C]56372.5833333333[/C][C]10766.1204834960[/C][C]31889[/C][/ROW]
[ROW][C]4[/C][C]47334.6666666667[/C][C]8976.30486167315[/C][C]25702[/C][/ROW]
[ROW][C]5[/C][C]36842.4166666667[/C][C]8181.3564607514[/C][C]24851[/C][/ROW]
[ROW][C]6[/C][C]34867.75[/C][C]7425.65676464807[/C][C]23341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41733&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41733&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
156294.083333333312367.820918219636059
25797110946.695117705633490
356372.583333333310766.120483496031889
447334.66666666678976.3048616731525702
536842.41666666678181.356460751424851
634867.757425.6567646480723341






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1600.52160862154
beta0.169360679208322
S.D.0.0336404548657977
T-STAT5.03443487562681
p-value0.00731063157370532

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1600.52160862154 \tabularnewline
beta & 0.169360679208322 \tabularnewline
S.D. & 0.0336404548657977 \tabularnewline
T-STAT & 5.03443487562681 \tabularnewline
p-value & 0.00731063157370532 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41733&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1600.52160862154[/C][/ROW]
[ROW][C]beta[/C][C]0.169360679208322[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0336404548657977[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.03443487562681[/C][/ROW]
[ROW][C]p-value[/C][C]0.00731063157370532[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41733&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41733&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)
alpha1600.52160862154
beta0.169360679208322
S.D.0.0336404548657977
T-STAT5.03443487562681
p-value0.00731063157370532






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.442910887457308
beta0.810952967830714
S.D.0.142492845546958
T-STAT5.69118375535191
p-value0.0047081370080060
Lambda0.189047032169286

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.442910887457308 \tabularnewline
beta & 0.810952967830714 \tabularnewline
S.D. & 0.142492845546958 \tabularnewline
T-STAT & 5.69118375535191 \tabularnewline
p-value & 0.0047081370080060 \tabularnewline
Lambda & 0.189047032169286 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41733&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.442910887457308[/C][/ROW]
[ROW][C]beta[/C][C]0.810952967830714[/C][/ROW]
[ROW][C]S.D.[/C][C]0.142492845546958[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.69118375535191[/C][/ROW]
[ROW][C]p-value[/C][C]0.0047081370080060[/C][/ROW]
[ROW][C]Lambda[/C][C]0.189047032169286[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41733&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41733&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)
alpha0.442910887457308
beta0.810952967830714
S.D.0.142492845546958
T-STAT5.69118375535191
p-value0.0047081370080060
Lambda0.189047032169286


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')