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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 computationTue, 24 Nov 2009 12:44:55 -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/24/t1259091934i5cwljej198pydb.htm/, Retrieved Sun, 16 Jun 2024 22:27:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59253, Retrieved Sun, 16 Jun 2024 22:27:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact213
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D          [Standard Deviation-Mean Plot] [] [2009-11-24 19:44:55] [7dd0431c761b876151627bfbf92230c8] [Current]
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Dataseries X:
90398
90269
90390
88219
87032
87175
92603
93571
94118
92159
89528
89955
89587
89488
88521
86587
85159
84915
91378
92729
92194
89664
86285
86858
87184
86629
85220
84816
84831
84957
90951
92134
91790
86625
83324
82719
83614
81640
78665
77828
75728
72187
79357
81329
77304
75576
72932
74291
74988
73302
70483
69848
66466
67610
75091
76207
73454
72008
71362
74250




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=59253&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=59253&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59253&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
190451.41666666672321.261704658737086
288613.752670.498868104137814
3867653208.206550820459415
477537.58333333333571.9945398088511427
572089.08333333333048.019042482079741

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 90451.4166666667 & 2321.26170465873 & 7086 \tabularnewline
2 & 88613.75 & 2670.49886810413 & 7814 \tabularnewline
3 & 86765 & 3208.20655082045 & 9415 \tabularnewline
4 & 77537.5833333333 & 3571.99453980885 & 11427 \tabularnewline
5 & 72089.0833333333 & 3048.01904248207 & 9741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59253&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]90451.4166666667[/C][C]2321.26170465873[/C][C]7086[/C][/ROW]
[ROW][C]2[/C][C]88613.75[/C][C]2670.49886810413[/C][C]7814[/C][/ROW]
[ROW][C]3[/C][C]86765[/C][C]3208.20655082045[/C][C]9415[/C][/ROW]
[ROW][C]4[/C][C]77537.5833333333[/C][C]3571.99453980885[/C][C]11427[/C][/ROW]
[ROW][C]5[/C][C]72089.0833333333[/C][C]3048.01904248207[/C][C]9741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59253&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59253&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
190451.41666666672321.261704658737086
288613.752670.498868104137814
3867653208.206550820459415
477537.58333333333571.9945398088511427
572089.08333333333048.019042482079741







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6205.59609178775
beta-0.0390124760327636
S.D.0.0272005098989981
T-STAT-1.43425532012547
p-value0.246971422133553

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6205.59609178775 \tabularnewline
beta & -0.0390124760327636 \tabularnewline
S.D. & 0.0272005098989981 \tabularnewline
T-STAT & -1.43425532012547 \tabularnewline
p-value & 0.246971422133553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59253&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6205.59609178775[/C][/ROW]
[ROW][C]beta[/C][C]-0.0390124760327636[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0272005098989981[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.43425532012547[/C][/ROW]
[ROW][C]p-value[/C][C]0.246971422133553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59253&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59253&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)
alpha6205.59609178775
beta-0.0390124760327636
S.D.0.0272005098989981
T-STAT-1.43425532012547
p-value0.246971422133553







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha20.2011252882635
beta-1.07893714056847
S.D.0.768520134522233
T-STAT-1.40391525491940
p-value0.254956749131866
Lambda2.07893714056847

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 20.2011252882635 \tabularnewline
beta & -1.07893714056847 \tabularnewline
S.D. & 0.768520134522233 \tabularnewline
T-STAT & -1.40391525491940 \tabularnewline
p-value & 0.254956749131866 \tabularnewline
Lambda & 2.07893714056847 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59253&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]20.2011252882635[/C][/ROW]
[ROW][C]beta[/C][C]-1.07893714056847[/C][/ROW]
[ROW][C]S.D.[/C][C]0.768520134522233[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.40391525491940[/C][/ROW]
[ROW][C]p-value[/C][C]0.254956749131866[/C][/ROW]
[ROW][C]Lambda[/C][C]2.07893714056847[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59253&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59253&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)
alpha20.2011252882635
beta-1.07893714056847
S.D.0.768520134522233
T-STAT-1.40391525491940
p-value0.254956749131866
Lambda2.07893714056847



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')