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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 25 Apr 2016 18:20:37 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/25/t1461604872ei07084vnrwgd19.htm/, Retrieved Sun, 05 May 2024 22:38:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294754, Retrieved Sun, 05 May 2024 22:38:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Opgave9/oef2-1] [2016-04-25 17:20:37] [efea2b8bc7c91838390b884e612c3e3f] [Current]
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Dataseries X:
92,94
92,97
93,37
92,6
92,84
92,55
92,93
92,44
93,36
93,24
92,65
92,06
92,88
91,69
91,66
90,26
91,11
92,33
91,82
92,24
93,35
93,53
93,34
92,59
92,42
92,64
94,44
93,59
93,39
93,33
93,72
95,43
97,06
97,7
97,59
96,97
97,75
99,27
100,63
99,8
99,5
99,72
99,77
100,18
101,11
100,67
101,13
100,46
101,6
102,3
103,26
104,56
104,61
104,62
105,03
104,93
104,73
104,33
104,6
104,41
104,63
105,55
106,12
106,62
106,72
106,52
106,79
106,95
106,92
106,74
108,13
107,86




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294754&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294754&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'Sir Maurice George Kendall' @ kendall.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
192.82916666666670.3920913236232171.31
292.23333333333330.9843533487277393.27
394.85666666666671.991072499174685.28
499.99916666666670.9349521945322153.38
5104.0816666666671.09889889793323.43000000000001
6106.6291666666670.9260812681139363.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 92.8291666666667 & 0.392091323623217 & 1.31 \tabularnewline
2 & 92.2333333333333 & 0.984353348727739 & 3.27 \tabularnewline
3 & 94.8566666666667 & 1.99107249917468 & 5.28 \tabularnewline
4 & 99.9991666666667 & 0.934952194532215 & 3.38 \tabularnewline
5 & 104.081666666667 & 1.0988988979332 & 3.43000000000001 \tabularnewline
6 & 106.629166666667 & 0.926081268113936 & 3.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294754&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]92.8291666666667[/C][C]0.392091323623217[/C][C]1.31[/C][/ROW]
[ROW][C]2[/C][C]92.2333333333333[/C][C]0.984353348727739[/C][C]3.27[/C][/ROW]
[ROW][C]3[/C][C]94.8566666666667[/C][C]1.99107249917468[/C][C]5.28[/C][/ROW]
[ROW][C]4[/C][C]99.9991666666667[/C][C]0.934952194532215[/C][C]3.38[/C][/ROW]
[ROW][C]5[/C][C]104.081666666667[/C][C]1.0988988979332[/C][C]3.43000000000001[/C][/ROW]
[ROW][C]6[/C][C]106.629166666667[/C][C]0.926081268113936[/C][C]3.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294754&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
192.82916666666670.3920913236232171.31
292.23333333333330.9843533487277393.27
394.85666666666671.991072499174685.28
499.99916666666670.9349521945322153.38
5104.0816666666671.09889889793323.43000000000001
6106.6291666666670.9260812681139363.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.15696653194079
beta-0.00104016139772939
S.D.0.0428630106427717
T-STAT-0.0242671100823572
p-value0.981801900018474

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.15696653194079 \tabularnewline
beta & -0.00104016139772939 \tabularnewline
S.D. & 0.0428630106427717 \tabularnewline
T-STAT & -0.0242671100823572 \tabularnewline
p-value & 0.981801900018474 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294754&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.15696653194079[/C][/ROW]
[ROW][C]beta[/C][C]-0.00104016139772939[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0428630106427717[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0242671100823572[/C][/ROW]
[ROW][C]p-value[/C][C]0.981801900018474[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294754&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294754&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)
alpha1.15696653194079
beta-0.00104016139772939
S.D.0.0428630106427717
T-STAT-0.0242671100823572
p-value0.981801900018474







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.89143060538262
beta1.49072789251212
S.D.4.17931844674734
T-STAT0.356691626040681
p-value0.739343125563286
Lambda-0.490727892512122

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.89143060538262 \tabularnewline
beta & 1.49072789251212 \tabularnewline
S.D. & 4.17931844674734 \tabularnewline
T-STAT & 0.356691626040681 \tabularnewline
p-value & 0.739343125563286 \tabularnewline
Lambda & -0.490727892512122 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294754&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.89143060538262[/C][/ROW]
[ROW][C]beta[/C][C]1.49072789251212[/C][/ROW]
[ROW][C]S.D.[/C][C]4.17931844674734[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.356691626040681[/C][/ROW]
[ROW][C]p-value[/C][C]0.739343125563286[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.490727892512122[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294754&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294754&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-6.89143060538262
beta1.49072789251212
S.D.4.17931844674734
T-STAT0.356691626040681
p-value0.739343125563286
Lambda-0.490727892512122



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')