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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 17 Dec 2008 09:55:27 -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/2008/Dec/17/t1229532963jocp9heikgbnk4i.htm/, Retrieved Sat, 18 May 2024 10:03:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34449, Retrieved Sat, 18 May 2024 10:03:49 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Standard Deviation-Mean Plot] [paper standart de...] [2008-12-03 13:08:33] [f58cc3b532da25682c394745f1a82535]
-         [Standard Deviation-Mean Plot] [] [2008-12-17 16:55:27] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34449&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34449&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34449&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12516.0675304.045920817743871.21
21944.51833333333141.731315769300485.63
32437.8275161.517349595808582.2
43100.70166666667137.836137815447446.05
53766.28333333333217.593686252542774.53
64433.40666666667166.292423614292497.21

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2516.0675 & 304.045920817743 & 871.21 \tabularnewline
2 & 1944.51833333333 & 141.731315769300 & 485.63 \tabularnewline
3 & 2437.8275 & 161.517349595808 & 582.2 \tabularnewline
4 & 3100.70166666667 & 137.836137815447 & 446.05 \tabularnewline
5 & 3766.28333333333 & 217.593686252542 & 774.53 \tabularnewline
6 & 4433.40666666667 & 166.292423614292 & 497.21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34449&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]2516.0675[/C][C]304.045920817743[/C][C]871.21[/C][/ROW]
[ROW][C]2[/C][C]1944.51833333333[/C][C]141.731315769300[/C][C]485.63[/C][/ROW]
[ROW][C]3[/C][C]2437.8275[/C][C]161.517349595808[/C][C]582.2[/C][/ROW]
[ROW][C]4[/C][C]3100.70166666667[/C][C]137.836137815447[/C][C]446.05[/C][/ROW]
[ROW][C]5[/C][C]3766.28333333333[/C][C]217.593686252542[/C][C]774.53[/C][/ROW]
[ROW][C]6[/C][C]4433.40666666667[/C][C]166.292423614292[/C][C]497.21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34449&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34449&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
12516.0675304.045920817743871.21
21944.51833333333141.731315769300485.63
32437.8275161.517349595808582.2
43100.70166666667137.836137815447446.05
53766.28333333333217.593686252542774.53
64433.40666666667166.292423614292497.21







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha192.363218566388
beta-0.00138264449414100
S.D.0.034200629166372
T-STAT-0.0404274578521642
p-value0.969689726215149

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 192.363218566388 \tabularnewline
beta & -0.00138264449414100 \tabularnewline
S.D. & 0.034200629166372 \tabularnewline
T-STAT & -0.0404274578521642 \tabularnewline
p-value & 0.969689726215149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34449&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]192.363218566388[/C][/ROW]
[ROW][C]beta[/C][C]-0.00138264449414100[/C][/ROW]
[ROW][C]S.D.[/C][C]0.034200629166372[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0404274578521642[/C][/ROW]
[ROW][C]p-value[/C][C]0.969689726215149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34449&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34449&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)
alpha192.363218566388
beta-0.00138264449414100
S.D.0.034200629166372
T-STAT-0.0404274578521642
p-value0.969689726215149







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.5435103625303
beta0.0818241532008829
S.D.0.495224450909668
T-STAT0.165226399969916
p-value0.87677997379623
Lambda0.918175846799117

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.5435103625303 \tabularnewline
beta & 0.0818241532008829 \tabularnewline
S.D. & 0.495224450909668 \tabularnewline
T-STAT & 0.165226399969916 \tabularnewline
p-value & 0.87677997379623 \tabularnewline
Lambda & 0.918175846799117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34449&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.5435103625303[/C][/ROW]
[ROW][C]beta[/C][C]0.0818241532008829[/C][/ROW]
[ROW][C]S.D.[/C][C]0.495224450909668[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.165226399969916[/C][/ROW]
[ROW][C]p-value[/C][C]0.87677997379623[/C][/ROW]
[ROW][C]Lambda[/C][C]0.918175846799117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34449&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34449&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)
alpha4.5435103625303
beta0.0818241532008829
S.D.0.495224450909668
T-STAT0.165226399969916
p-value0.87677997379623
Lambda0.918175846799117



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')