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Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 20 Dec 2012 08:26:08 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/20/t1356010012p3cbi9x58x4t1f6.htm/, Retrieved Fri, 29 Mar 2024 12:32:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=202672, Retrieved Fri, 29 Mar 2024 12:32:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2012-12-20 13:26:08] [14d0a7ecb926325afa0eb6a607fbc7a0] [Current]
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Dataseries X:
26,81
28.24
27,58
27.98
27.84
27,49
26.97
27.71
27.46
27.04
28.00
27.32
26.36
26.15
25.94
24,00
24.32
23.10
22.92
23,56
22.17
22.36
19.86
20.07
19.21
19.99
20.47
21,17
21.25
21.18
21.21
21.11
21,94
22.56
23,23
19.50
19,32
19.00
18,98
19.88
19.48
19.52
19,52
19.75
19.64
20,23
20.40
20.91
21,95
21.83
22.27
21.99
21.66
20.32
20.62
20.28
20.79
22.86
22.59
23.29
21.87
21.52
22.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202672&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202672&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202672&T=0

As an alternative you can also use a 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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
127.65250.6238255632252771.43
227.50250.3832644865711760.870000000000001
327.4550.4031128874149280.960000000000001
425.61251.08858853567362.36
523.4750.6244731112439241.4
621.1151.332929105391582.5
720.210.8241359111214611.96
821.18750.05909032633745320.140000000000001
921.80751.626025317556073.73
1019.2950.4199603155854920.899999999999999
1119.56750.1231191834497510.27
1220.2950.5236092690801671.27
1322.010.1861898672502530.440000000000001
1420.720.6447738621666771.38
1522.38251.10010226797332.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 27.6525 & 0.623825563225277 & 1.43 \tabularnewline
2 & 27.5025 & 0.383264486571176 & 0.870000000000001 \tabularnewline
3 & 27.455 & 0.403112887414928 & 0.960000000000001 \tabularnewline
4 & 25.6125 & 1.0885885356736 & 2.36 \tabularnewline
5 & 23.475 & 0.624473111243924 & 1.4 \tabularnewline
6 & 21.115 & 1.33292910539158 & 2.5 \tabularnewline
7 & 20.21 & 0.824135911121461 & 1.96 \tabularnewline
8 & 21.1875 & 0.0590903263374532 & 0.140000000000001 \tabularnewline
9 & 21.8075 & 1.62602531755607 & 3.73 \tabularnewline
10 & 19.295 & 0.419960315585492 & 0.899999999999999 \tabularnewline
11 & 19.5675 & 0.123119183449751 & 0.27 \tabularnewline
12 & 20.295 & 0.523609269080167 & 1.27 \tabularnewline
13 & 22.01 & 0.186189867250253 & 0.440000000000001 \tabularnewline
14 & 20.72 & 0.644773862166677 & 1.38 \tabularnewline
15 & 22.3825 & 1.1001022679733 & 2.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202672&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]27.6525[/C][C]0.623825563225277[/C][C]1.43[/C][/ROW]
[ROW][C]2[/C][C]27.5025[/C][C]0.383264486571176[/C][C]0.870000000000001[/C][/ROW]
[ROW][C]3[/C][C]27.455[/C][C]0.403112887414928[/C][C]0.960000000000001[/C][/ROW]
[ROW][C]4[/C][C]25.6125[/C][C]1.0885885356736[/C][C]2.36[/C][/ROW]
[ROW][C]5[/C][C]23.475[/C][C]0.624473111243924[/C][C]1.4[/C][/ROW]
[ROW][C]6[/C][C]21.115[/C][C]1.33292910539158[/C][C]2.5[/C][/ROW]
[ROW][C]7[/C][C]20.21[/C][C]0.824135911121461[/C][C]1.96[/C][/ROW]
[ROW][C]8[/C][C]21.1875[/C][C]0.0590903263374532[/C][C]0.140000000000001[/C][/ROW]
[ROW][C]9[/C][C]21.8075[/C][C]1.62602531755607[/C][C]3.73[/C][/ROW]
[ROW][C]10[/C][C]19.295[/C][C]0.419960315585492[/C][C]0.899999999999999[/C][/ROW]
[ROW][C]11[/C][C]19.5675[/C][C]0.123119183449751[/C][C]0.27[/C][/ROW]
[ROW][C]12[/C][C]20.295[/C][C]0.523609269080167[/C][C]1.27[/C][/ROW]
[ROW][C]13[/C][C]22.01[/C][C]0.186189867250253[/C][C]0.440000000000001[/C][/ROW]
[ROW][C]14[/C][C]20.72[/C][C]0.644773862166677[/C][C]1.38[/C][/ROW]
[ROW][C]15[/C][C]22.3825[/C][C]1.1001022679733[/C][C]2.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202672&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202672&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
127.65250.6238255632252771.43
227.50250.3832644865711760.870000000000001
327.4550.4031128874149280.960000000000001
425.61251.08858853567362.36
523.4750.6244731112439241.4
621.1151.332929105391582.5
720.210.8241359111214611.96
821.18750.05909032633745320.140000000000001
921.80751.626025317556073.73
1019.2950.4199603155854920.899999999999999
1119.56750.1231191834497510.27
1220.2950.5236092690801671.27
1322.010.1861898672502530.440000000000001
1420.720.6447738621666771.38
1522.38251.10010226797332.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.644286186382063
beta0.000878396104206509
S.D.0.042520075251927
T-STAT0.0206583854568014
p-value0.983831879598336

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.644286186382063 \tabularnewline
beta & 0.000878396104206509 \tabularnewline
S.D. & 0.042520075251927 \tabularnewline
T-STAT & 0.0206583854568014 \tabularnewline
p-value & 0.983831879598336 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202672&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.644286186382063[/C][/ROW]
[ROW][C]beta[/C][C]0.000878396104206509[/C][/ROW]
[ROW][C]S.D.[/C][C]0.042520075251927[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0206583854568014[/C][/ROW]
[ROW][C]p-value[/C][C]0.983831879598336[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202672&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202672&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.644286186382063
beta0.000878396104206509
S.D.0.042520075251927
T-STAT0.0206583854568014
p-value0.983831879598336







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.20665398296686
beta1.12373178580781
S.D.1.98287338118824
T-STAT0.566718882036942
p-value0.580558590086902
Lambda-0.12373178580781

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.20665398296686 \tabularnewline
beta & 1.12373178580781 \tabularnewline
S.D. & 1.98287338118824 \tabularnewline
T-STAT & 0.566718882036942 \tabularnewline
p-value & 0.580558590086902 \tabularnewline
Lambda & -0.12373178580781 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202672&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.20665398296686[/C][/ROW]
[ROW][C]beta[/C][C]1.12373178580781[/C][/ROW]
[ROW][C]S.D.[/C][C]1.98287338118824[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.566718882036942[/C][/ROW]
[ROW][C]p-value[/C][C]0.580558590086902[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.12373178580781[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202672&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202672&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.20665398296686
beta1.12373178580781
S.D.1.98287338118824
T-STAT0.566718882036942
p-value0.580558590086902
Lambda-0.12373178580781



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')