Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 04 Jan 2010 14:52:48 -0700
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/Jan/04/t1262642030ksgdlgwm0uvtsnw.htm/, Retrieved Fri, 03 May 2024 14:58:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71604, Retrieved Fri, 03 May 2024 14:58:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact165
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [opgave 8 eigen re...] [2010-01-04 21:52:48] [4c49eeca41cf2bf23e101541a1a2b4ce] [Current]
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Dataseries X:
203.7
173.8
167.1
151.8
144.5
128.4
121.6
124.9
122.7
148.1
176.9
234.6
254.6
279.7
275.8
283
295.4
297.6
276.8
250.1
239.1
258.9
276.1
264.1
265.5
287.7
285.1
304.5
301.5
274.2
258.6
253.9
269.6
266.9
269.6
257.9
258.2
254.7
237.2
267.2
228.8
196.3
194.8
186.6
176.7
162.1
154.9
150.1
150.5
143.6
143.8
141.5
147.9
151.4
144.6
140.4
139.5
138.1
136.7
130
128.5
130.4
125.7
121.7
129.9
129.6
128.2
119.7
112.2
105.6
101.2
94.9
95.1
93.1
91.4
89.8
85.9
89.7
91.6
88.6
86.9
86.4
82.2
81.5
81.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71604&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]3 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=71604&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71604&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1158.17535.0413554376695113
2270.93333333333317.895267700166058.5
3274.58333333333316.665469653984550.6
4205.63333333333342.0511016682697117.1
5142.3333333333336.0528480649170221.4
6118.96666666666712.475891903502535.5
788.51666666666674.1373758335300913.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 158.175 & 35.0413554376695 & 113 \tabularnewline
2 & 270.933333333333 & 17.8952677001660 & 58.5 \tabularnewline
3 & 274.583333333333 & 16.6654696539845 & 50.6 \tabularnewline
4 & 205.633333333333 & 42.0511016682697 & 117.1 \tabularnewline
5 & 142.333333333333 & 6.05284806491702 & 21.4 \tabularnewline
6 & 118.966666666667 & 12.4758919035025 & 35.5 \tabularnewline
7 & 88.5166666666667 & 4.13737583353009 & 13.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71604&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]158.175[/C][C]35.0413554376695[/C][C]113[/C][/ROW]
[ROW][C]2[/C][C]270.933333333333[/C][C]17.8952677001660[/C][C]58.5[/C][/ROW]
[ROW][C]3[/C][C]274.583333333333[/C][C]16.6654696539845[/C][C]50.6[/C][/ROW]
[ROW][C]4[/C][C]205.633333333333[/C][C]42.0511016682697[/C][C]117.1[/C][/ROW]
[ROW][C]5[/C][C]142.333333333333[/C][C]6.05284806491702[/C][C]21.4[/C][/ROW]
[ROW][C]6[/C][C]118.966666666667[/C][C]12.4758919035025[/C][C]35.5[/C][/ROW]
[ROW][C]7[/C][C]88.5166666666667[/C][C]4.13737583353009[/C][C]13.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71604&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71604&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
1158.17535.0413554376695113
2270.93333333333317.895267700166058.5
3274.58333333333316.665469653984550.6
4205.63333333333342.0511016682697117.1
5142.3333333333336.0528480649170221.4
6118.96666666666712.475891903502535.5
788.51666666666674.1373758335300913.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.96440511154514
beta0.0679577816749956
S.D.0.0823007935852183
T-STAT0.825724500513215
p-value0.446555488380940

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.96440511154514 \tabularnewline
beta & 0.0679577816749956 \tabularnewline
S.D. & 0.0823007935852183 \tabularnewline
T-STAT & 0.825724500513215 \tabularnewline
p-value & 0.446555488380940 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71604&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.96440511154514[/C][/ROW]
[ROW][C]beta[/C][C]0.0679577816749956[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0823007935852183[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.825724500513215[/C][/ROW]
[ROW][C]p-value[/C][C]0.446555488380940[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71604&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71604&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)
alpha6.96440511154514
beta0.0679577816749956
S.D.0.0823007935852183
T-STAT0.825724500513215
p-value0.446555488380940







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.68453391219817
beta1.24289653347654
S.D.0.707319317041133
T-STAT1.75719297286527
p-value0.139225956424825
Lambda-0.242896533476538

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.68453391219817 \tabularnewline
beta & 1.24289653347654 \tabularnewline
S.D. & 0.707319317041133 \tabularnewline
T-STAT & 1.75719297286527 \tabularnewline
p-value & 0.139225956424825 \tabularnewline
Lambda & -0.242896533476538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71604&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.68453391219817[/C][/ROW]
[ROW][C]beta[/C][C]1.24289653347654[/C][/ROW]
[ROW][C]S.D.[/C][C]0.707319317041133[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.75719297286527[/C][/ROW]
[ROW][C]p-value[/C][C]0.139225956424825[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.242896533476538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71604&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71604&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-3.68453391219817
beta1.24289653347654
S.D.0.707319317041133
T-STAT1.75719297286527
p-value0.139225956424825
Lambda-0.242896533476538



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')