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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, 23 Nov 2007 07:07:57 -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/2007/Nov/23/t1195826472cd6p3f41uxv52fi.htm/, Retrieved Mon, 29 Apr 2024 00:44:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6177, Retrieved Mon, 29 Apr 2024 00:44:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2007-11-23 14:07:57] [a1fadf46580e43815db2830b4560d35f] [Current]
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Dataseries X:
82.9
83.8
86.2
86.1
86.2
88.8
89.6
87.8
88.3
88.6
91
91.5
95.4
98.7
99.9
98.6
100.3
100.2
100.4
101.4
103
109.1
111.4
114.1
121.8
127.6
129.9
128
123.5
124
127.4
127.6
128.4
131.4
135.1
134
144.5
147.3
150.9
148.7
141.4
138.9
139.8
145.6
147.9
148.5
151.1
157.5
167.5
172.3
173.5
187.5
205.5
195.1
204.5
204.5
201.7
207
206.6
210.6
211.1




Summary of compuational 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 compuational 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=6177&T=0

[TABLE]
[ROW][C]Summary of compuational 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=6177&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6177&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 compuational 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
187.56666666666672.635882923780728.6
2102.7083333333335.7178283120482530.3
3128.2254.0057061572439248.9
4146.8416666666675.2659210250842471.4
5194.69166666666715.5109028125576124.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 87.5666666666667 & 2.63588292378072 & 8.6 \tabularnewline
2 & 102.708333333333 & 5.71782831204825 & 30.3 \tabularnewline
3 & 128.225 & 4.00570615724392 & 48.9 \tabularnewline
4 & 146.841666666667 & 5.26592102508424 & 71.4 \tabularnewline
5 & 194.691666666667 & 15.5109028125576 & 124.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6177&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]87.5666666666667[/C][C]2.63588292378072[/C][C]8.6[/C][/ROW]
[ROW][C]2[/C][C]102.708333333333[/C][C]5.71782831204825[/C][C]30.3[/C][/ROW]
[ROW][C]3[/C][C]128.225[/C][C]4.00570615724392[/C][C]48.9[/C][/ROW]
[ROW][C]4[/C][C]146.841666666667[/C][C]5.26592102508424[/C][C]71.4[/C][/ROW]
[ROW][C]5[/C][C]194.691666666667[/C][C]15.5109028125576[/C][C]124.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6177&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6177&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
187.56666666666672.635882923780728.6
2102.7083333333335.7178283120482530.3
3128.2254.0057061572439248.9
4146.8416666666675.2659210250842471.4
5194.69166666666715.5109028125576124.4







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-7.53372853790361
beta0.107274709237260
S.D.0.0337295839815053
T-STAT3.18043380837667
p-value0.0500773314772986

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -7.53372853790361 \tabularnewline
beta & 0.107274709237260 \tabularnewline
S.D. & 0.0337295839815053 \tabularnewline
T-STAT & 3.18043380837667 \tabularnewline
p-value & 0.0500773314772986 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6177&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.53372853790361[/C][/ROW]
[ROW][C]beta[/C][C]0.107274709237260[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0337295839815053[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.18043380837667[/C][/ROW]
[ROW][C]p-value[/C][C]0.0500773314772986[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6177&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6177&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-7.53372853790361
beta0.107274709237260
S.D.0.0337295839815053
T-STAT3.18043380837667
p-value0.0500773314772986







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-7.04599630171954
beta1.80575476978202
S.D.0.628034836868187
T-STAT2.87524618663951
p-value0.0637761745376771
Lambda-0.80575476978202

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.04599630171954 \tabularnewline
beta & 1.80575476978202 \tabularnewline
S.D. & 0.628034836868187 \tabularnewline
T-STAT & 2.87524618663951 \tabularnewline
p-value & 0.0637761745376771 \tabularnewline
Lambda & -0.80575476978202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6177&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.04599630171954[/C][/ROW]
[ROW][C]beta[/C][C]1.80575476978202[/C][/ROW]
[ROW][C]S.D.[/C][C]0.628034836868187[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.87524618663951[/C][/ROW]
[ROW][C]p-value[/C][C]0.0637761745376771[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.80575476978202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6177&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6177&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-7.04599630171954
beta1.80575476978202
S.D.0.628034836868187
T-STAT2.87524618663951
p-value0.0637761745376771
Lambda-0.80575476978202



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')