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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 04:39:37 -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/2013/Dec/05/t138623639278xotulgvfueoeh.htm/, Retrieved Sat, 20 Apr 2024 14:22:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230891, Retrieved Sat, 20 Apr 2024 14:22:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Motorfietsen en s...] [2013-12-05 09:39:37] [3d5e85e1419377f0daeb0f510d27f47a] [Current]
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Dataseries X:
1876.88
1876.68
1865.52
1858.99
1856.87
1858.22
1858.22
1859.32
1859.52
1852.48
1850.07
1850.07
1850.07
1841.55
1845
1844.01
1842.67
1842.67
1842.67
1842.9
1840.37
1841.59
1844.33
1844.33
1844.33
1845.39
1861.84
1862.85
1869.46
1870.8
1870.8
1871.52
1875.52
1880.38
1885.05
1886.42
1886.42
1891.65
1903.11
1905.29
1904.26
1905.37
1905.37
1905.12
1908.62
1915.08
1916.36
1916.68
1916.24
1922.05
1922.63
1922.47
1920.64
1920.66
1920.66
1921.19
1921.44
1921.73
1921.81
1921.81
1921.81
1921.48
1917.07
1912.64
1901.15
1898.12
1900.02
1900.02
1900.82
1901.9
1902.19
1901.84




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230891&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]4 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=230891&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230891&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11860.236666666678.8654685907364326.8100000000002
21843.513333333332.462904173876239.70000000000005
31868.6966666666713.48447142816442.0900000000001
41905.27759.0813976947884230.26
51921.110833333331.675114423952386.3900000000001
61906.588333333338.9679690954513123.6900000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1860.23666666667 & 8.86546859073643 & 26.8100000000002 \tabularnewline
2 & 1843.51333333333 & 2.46290417387623 & 9.70000000000005 \tabularnewline
3 & 1868.69666666667 & 13.484471428164 & 42.0900000000001 \tabularnewline
4 & 1905.2775 & 9.08139769478842 & 30.26 \tabularnewline
5 & 1921.11083333333 & 1.67511442395238 & 6.3900000000001 \tabularnewline
6 & 1906.58833333333 & 8.96796909545131 & 23.6900000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230891&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]1860.23666666667[/C][C]8.86546859073643[/C][C]26.8100000000002[/C][/ROW]
[ROW][C]2[/C][C]1843.51333333333[/C][C]2.46290417387623[/C][C]9.70000000000005[/C][/ROW]
[ROW][C]3[/C][C]1868.69666666667[/C][C]13.484471428164[/C][C]42.0900000000001[/C][/ROW]
[ROW][C]4[/C][C]1905.2775[/C][C]9.08139769478842[/C][C]30.26[/C][/ROW]
[ROW][C]5[/C][C]1921.11083333333[/C][C]1.67511442395238[/C][C]6.3900000000001[/C][/ROW]
[ROW][C]6[/C][C]1906.58833333333[/C][C]8.96796909545131[/C][C]23.6900000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230891&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230891&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
11860.236666666678.8654685907364326.8100000000002
21843.513333333332.462904173876239.70000000000005
31868.6966666666713.48447142816442.0900000000001
41905.27759.0813976947884230.26
51921.110833333331.675114423952386.3900000000001
61906.588333333338.9679690954513123.6900000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha34.7700095520722
beta-0.0145136300576801
S.D.0.0725498991533624
T-STAT-0.200050313329863
p-value0.85120020647889

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 34.7700095520722 \tabularnewline
beta & -0.0145136300576801 \tabularnewline
S.D. & 0.0725498991533624 \tabularnewline
T-STAT & -0.200050313329863 \tabularnewline
p-value & 0.85120020647889 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230891&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]34.7700095520722[/C][/ROW]
[ROW][C]beta[/C][C]-0.0145136300576801[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0725498991533624[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.200050313329863[/C][/ROW]
[ROW][C]p-value[/C][C]0.85120020647889[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230891&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230891&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)
alpha34.7700095520722
beta-0.0145136300576801
S.D.0.0725498991533624
T-STAT-0.200050313329863
p-value0.85120020647889







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha44.5992397441461
beta-5.67981625247779
S.D.25.5296599733015
T-STAT-0.222479118735528
p-value0.834839228594918
Lambda6.67981625247779

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 44.5992397441461 \tabularnewline
beta & -5.67981625247779 \tabularnewline
S.D. & 25.5296599733015 \tabularnewline
T-STAT & -0.222479118735528 \tabularnewline
p-value & 0.834839228594918 \tabularnewline
Lambda & 6.67981625247779 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230891&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]44.5992397441461[/C][/ROW]
[ROW][C]beta[/C][C]-5.67981625247779[/C][/ROW]
[ROW][C]S.D.[/C][C]25.5296599733015[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.222479118735528[/C][/ROW]
[ROW][C]p-value[/C][C]0.834839228594918[/C][/ROW]
[ROW][C]Lambda[/C][C]6.67981625247779[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230891&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230891&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)
alpha44.5992397441461
beta-5.67981625247779
S.D.25.5296599733015
T-STAT-0.222479118735528
p-value0.834839228594918
Lambda6.67981625247779



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')