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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 19 Mar 2016 22:38:59 +0000
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/Mar/19/t1458427171bn603tyjoez2xwz.htm/, Retrieved Tue, 07 May 2024 18:30:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294362, Retrieved Tue, 07 May 2024 18:30:23 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2016-03-19 22:38:59] [bfab382a4ab6d7836f6b75894769f754] [Current]
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Dataseries X:
100
99
99.3
99.5
100.7
102.9
101.2
99.5
99.5
99.5
99.4
99.5
99.7
99.8
99.8
100.1
100
100
100.1
100.1
100
99.9
99.9
99.8
100.4
102.2
103.1
103
102.9
102.8
103
103.5
103.6
103.2
103
103
106.1
104.8
105.3
106.3
107.9
106.1
106.8
108.7
110.8
111.8
111.3
111.7
110.8
110.3
110.5
110.5
112.5
113
113.5
112.8
109.5
111.5
111.5
111.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294362&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294362&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294362&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'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11001.105358847532413.90000000000001
299.93333333333330.1370688833684670.399999999999991
3102.8083333333330.8349832152187053.19999999999999
4108.1333333333332.632431759741747
5111.4666666666671.241211529355924

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100 & 1.10535884753241 & 3.90000000000001 \tabularnewline
2 & 99.9333333333333 & 0.137068883368467 & 0.399999999999991 \tabularnewline
3 & 102.808333333333 & 0.834983215218705 & 3.19999999999999 \tabularnewline
4 & 108.133333333333 & 2.63243175974174 & 7 \tabularnewline
5 & 111.466666666667 & 1.24121152935592 & 4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294362&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]100[/C][C]1.10535884753241[/C][C]3.90000000000001[/C][/ROW]
[ROW][C]2[/C][C]99.9333333333333[/C][C]0.137068883368467[/C][C]0.399999999999991[/C][/ROW]
[ROW][C]3[/C][C]102.808333333333[/C][C]0.834983215218705[/C][C]3.19999999999999[/C][/ROW]
[ROW][C]4[/C][C]108.133333333333[/C][C]2.63243175974174[/C][C]7[/C][/ROW]
[ROW][C]5[/C][C]111.466666666667[/C][C]1.24121152935592[/C][C]4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294362&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294362&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
11001.105358847532413.90000000000001
299.93333333333330.1370688833684670.399999999999991
3102.8083333333330.8349832152187053.19999999999999
4108.1333333333332.632431759741747
5111.4666666666671.241211529355924







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-10.064928920403
beta0.107737334446928
S.D.0.0813459922399058
T-STAT1.3244332201295
p-value0.27721734654135

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -10.064928920403 \tabularnewline
beta & 0.107737334446928 \tabularnewline
S.D. & 0.0813459922399058 \tabularnewline
T-STAT & 1.3244332201295 \tabularnewline
p-value & 0.27721734654135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294362&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.064928920403[/C][/ROW]
[ROW][C]beta[/C][C]0.107737334446928[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0813459922399058[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.3244332201295[/C][/ROW]
[ROW][C]p-value[/C][C]0.27721734654135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294362&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294362&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-10.064928920403
beta0.107737334446928
S.D.0.0813459922399058
T-STAT1.3244332201295
p-value0.27721734654135







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-65.190844499736
beta13.9877771664405
S.D.10.1694419309986
T-STAT1.37547146257876
p-value0.262695696711821
Lambda-12.9877771664405

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -65.190844499736 \tabularnewline
beta & 13.9877771664405 \tabularnewline
S.D. & 10.1694419309986 \tabularnewline
T-STAT & 1.37547146257876 \tabularnewline
p-value & 0.262695696711821 \tabularnewline
Lambda & -12.9877771664405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294362&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-65.190844499736[/C][/ROW]
[ROW][C]beta[/C][C]13.9877771664405[/C][/ROW]
[ROW][C]S.D.[/C][C]10.1694419309986[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.37547146257876[/C][/ROW]
[ROW][C]p-value[/C][C]0.262695696711821[/C][/ROW]
[ROW][C]Lambda[/C][C]-12.9877771664405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294362&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294362&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-65.190844499736
beta13.9877771664405
S.D.10.1694419309986
T-STAT1.37547146257876
p-value0.262695696711821
Lambda-12.9877771664405



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')