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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 21 Dec 2012 14:28:38 -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/21/t1356118132ja56oxxarq16nmr.htm/, Retrieved Thu, 25 Apr 2024 10:20:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204143, Retrieved Thu, 25 Apr 2024 10:20:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [Boxplot gemiddeld...] [2012-10-05 17:50:48] [414c2ec381eb4adb801f9ac6823317d8]
- RMPD  [Harrell-Davis Quantiles] [Decielen inschrij...] [2012-10-05 17:57:24] [414c2ec381eb4adb801f9ac6823317d8]
- R P     [Harrell-Davis Quantiles] [Harrell-Davis Per...] [2012-10-08 07:03:49] [414c2ec381eb4adb801f9ac6823317d8]
- RMPD        [Standard Deviation-Mean Plot] [] [2012-12-21 19:28:38] [a5163a6b16cb463ddc5e8265592a0086] [Current]
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Dataseries X:
299.81
299.01
296.82
296.67
296.95
296.80
296.80
295.93
293.77
291.02
288.61
284.55
284.55
278.14
273.28
270.14
268.36
267.15
267.15
265.47
261.75
256.51
252.98
251.17
251.17
244.27
240.54
238.92
237.47
235.91
235.91
231.41
224.94
222.19
219.06
217.83
217.83
216.89
213.84
212.90
213.98
215.31
215.31
214.09
213.71
211.54
209.40
207.33
207.33
202.75
200.26
198.99
198.82
198.43
198.43
195.68
195.45
193.65
191.38
189.71
189.71
185.49
183.01
182.38
181.60
182.13
182.13
180.81
180.25
179.84
178.50
178.11




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204143&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204143&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204143&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1294.7283333333334.5021930682993215.26
2266.38759.8437133837702833.38
3233.30166666666710.41714132251933.34
4213.5108333333332.9635741883234410.5
5197.5733333333334.8421695613233217.62
6181.9966666666673.1552073360293411.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 294.728333333333 & 4.50219306829932 & 15.26 \tabularnewline
2 & 266.3875 & 9.84371338377028 & 33.38 \tabularnewline
3 & 233.301666666667 & 10.417141322519 & 33.34 \tabularnewline
4 & 213.510833333333 & 2.96357418832344 & 10.5 \tabularnewline
5 & 197.573333333333 & 4.84216956132332 & 17.62 \tabularnewline
6 & 181.996666666667 & 3.15520733602934 & 11.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204143&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]294.728333333333[/C][C]4.50219306829932[/C][C]15.26[/C][/ROW]
[ROW][C]2[/C][C]266.3875[/C][C]9.84371338377028[/C][C]33.38[/C][/ROW]
[ROW][C]3[/C][C]233.301666666667[/C][C]10.417141322519[/C][C]33.34[/C][/ROW]
[ROW][C]4[/C][C]213.510833333333[/C][C]2.96357418832344[/C][C]10.5[/C][/ROW]
[ROW][C]5[/C][C]197.573333333333[/C][C]4.84216956132332[/C][C]17.62[/C][/ROW]
[ROW][C]6[/C][C]181.996666666667[/C][C]3.15520733602934[/C][C]11.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204143&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204143&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
1294.7283333333334.5021930682993215.26
2266.38759.8437133837702833.38
3233.30166666666710.41714132251933.34
4213.5108333333332.9635741883234410.5
5197.5733333333334.8421695613233217.62
6181.9966666666673.1552073360293411.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.17881286659021
beta0.0308446324090282
S.D.0.0356462856323867
T-STAT0.865297235373216
p-value0.435686453623017

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.17881286659021 \tabularnewline
beta & 0.0308446324090282 \tabularnewline
S.D. & 0.0356462856323867 \tabularnewline
T-STAT & 0.865297235373216 \tabularnewline
p-value & 0.435686453623017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204143&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.17881286659021[/C][/ROW]
[ROW][C]beta[/C][C]0.0308446324090282[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0356462856323867[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.865297235373216[/C][/ROW]
[ROW][C]p-value[/C][C]0.435686453623017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204143&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204143&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)
alpha-1.17881286659021
beta0.0308446324090282
S.D.0.0356462856323867
T-STAT0.865297235373216
p-value0.435686453623017







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.11444798812073
beta1.43150608245983
S.D.1.30951412079727
T-STAT1.09315818724298
p-value0.33574349063
Lambda-0.431506082459833

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.11444798812073 \tabularnewline
beta & 1.43150608245983 \tabularnewline
S.D. & 1.30951412079727 \tabularnewline
T-STAT & 1.09315818724298 \tabularnewline
p-value & 0.33574349063 \tabularnewline
Lambda & -0.431506082459833 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204143&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.11444798812073[/C][/ROW]
[ROW][C]beta[/C][C]1.43150608245983[/C][/ROW]
[ROW][C]S.D.[/C][C]1.30951412079727[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.09315818724298[/C][/ROW]
[ROW][C]p-value[/C][C]0.33574349063[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.431506082459833[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204143&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204143&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-6.11444798812073
beta1.43150608245983
S.D.1.30951412079727
T-STAT1.09315818724298
p-value0.33574349063
Lambda-0.431506082459833



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')