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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 26 Nov 2009 16:17:39 -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/2009/Nov/27/t12592776491fr2quatxd8c1h9.htm/, Retrieved Sun, 28 Apr 2024 22:12:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60449, Retrieved Sun, 28 Apr 2024 22:12:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [SMP] [2009-11-26 23:17:39] [e458b4e05bf28a297f8af8d9f96e59d6] [Current]
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Dataseries X:
96.2
96.8
109.9
88
91.1
106.4
68.6
100.1
108
106
108.6
91.5
99.2
98
96.6
102.8
96.9
110
70.5
101.9
109.6
107.8
113
93.8
108
102.8
116.3
89.2
106.7
112.1
74.2
108.8
111.5
118.8
118.9
97.6
116.4
107.9
121.2
97.9
113.4
117.6
79.6
115.9
115.7
129.1
123.3
96.7
121.2
118.2
102.1
125.4
116.7
121.3
85.3
114.2
124.4
131
118.3
99.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60449&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60449&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60449&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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
197.611.870207166760741.3
2100.00833333333311.151637330523042.5
3105.40833333333313.094791354048444.7
4111.22513.746346622086449.5
5114.80833333333312.935255441363945.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 97.6 & 11.8702071667607 & 41.3 \tabularnewline
2 & 100.008333333333 & 11.1516373305230 & 42.5 \tabularnewline
3 & 105.408333333333 & 13.0947913540484 & 44.7 \tabularnewline
4 & 111.225 & 13.7463466220864 & 49.5 \tabularnewline
5 & 114.808333333333 & 12.9352554413639 & 45.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60449&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]97.6[/C][C]11.8702071667607[/C][C]41.3[/C][/ROW]
[ROW][C]2[/C][C]100.008333333333[/C][C]11.1516373305230[/C][C]42.5[/C][/ROW]
[ROW][C]3[/C][C]105.408333333333[/C][C]13.0947913540484[/C][C]44.7[/C][/ROW]
[ROW][C]4[/C][C]111.225[/C][C]13.7463466220864[/C][C]49.5[/C][/ROW]
[ROW][C]5[/C][C]114.808333333333[/C][C]12.9352554413639[/C][C]45.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60449&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60449&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
197.611.870207166760741.3
2100.00833333333311.151637330523042.5
3105.40833333333313.094791354048444.7
4111.22513.746346622086449.5
5114.80833333333312.935255441363945.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.84395402344044
beta0.110723878267801
S.D.0.0517654850927731
T-STAT2.13895181450273
p-value0.121973840080864

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.84395402344044 \tabularnewline
beta & 0.110723878267801 \tabularnewline
S.D. & 0.0517654850927731 \tabularnewline
T-STAT & 2.13895181450273 \tabularnewline
p-value & 0.121973840080864 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60449&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.84395402344044[/C][/ROW]
[ROW][C]beta[/C][C]0.110723878267801[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0517654850927731[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.13895181450273[/C][/ROW]
[ROW][C]p-value[/C][C]0.121973840080864[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60449&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60449&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)
alpha0.84395402344044
beta0.110723878267801
S.D.0.0517654850927731
T-STAT2.13895181450273
p-value0.121973840080864







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.91913310414065
beta0.954308178534045
S.D.0.438557847152433
T-STAT2.17601437240353
p-value0.117788780331108
Lambda0.0456918214659553

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.91913310414065 \tabularnewline
beta & 0.954308178534045 \tabularnewline
S.D. & 0.438557847152433 \tabularnewline
T-STAT & 2.17601437240353 \tabularnewline
p-value & 0.117788780331108 \tabularnewline
Lambda & 0.0456918214659553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60449&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.91913310414065[/C][/ROW]
[ROW][C]beta[/C][C]0.954308178534045[/C][/ROW]
[ROW][C]S.D.[/C][C]0.438557847152433[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.17601437240353[/C][/ROW]
[ROW][C]p-value[/C][C]0.117788780331108[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0456918214659553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60449&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60449&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-1.91913310414065
beta0.954308178534045
S.D.0.438557847152433
T-STAT2.17601437240353
p-value0.117788780331108
Lambda0.0456918214659553



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')