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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, 10 Dec 2009 05:26:00 -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/Dec/10/t1260448066y5emei96hfuoxtj.htm/, Retrieved Fri, 19 Apr 2024 03:17:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65309, Retrieved Fri, 19 Apr 2024 03:17:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D    [Standard Deviation-Mean Plot] [WS 9: Standard De...] [2009-12-04 13:47:20] [f924a0adda9c1905a1ba8f1c751261ff]
-    D        [Standard Deviation-Mean Plot] [xt standard devia...] [2009-12-10 12:26:00] [ac86848d66148c9c4c9404e0c9a511eb] [Current]
- R  D          [Standard Deviation-Mean Plot] [] [2009-12-11 15:14:16] [2c5be225250d91402426bbbf07a5e2b3]
- R  D          [Standard Deviation-Mean Plot] [] [2009-12-11 15:14:16] [2c5be225250d91402426bbbf07a5e2b3]
- R  D          [Standard Deviation-Mean Plot] [] [2009-12-11 15:14:16] [2c5be225250d91402426bbbf07a5e2b3]
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Dataseries X:
109.87
95.74
123.06
123.39
120.28
115.33
110.4
114.49
132.03
123.16
118.82
128.32
112.24
104.53
132.57
122.52
131.8
124.55
120.96
122.6
145.52
118.57
134.25
136.7
121.37
111.63
134.42
137.65
137.86
119.77
130.69
128.28
147.45
128.42
136.9
143.95
135.64
122.48
136.83
153.04
142.71
123.46
144.37
146.15
147.61
158.51
147.4
165.05
154.64
126.2
157.36
154.15
123.21
113.07
110.45
113.57
122.44
114.93
111.85
126.04




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=65309&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=65309&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65309&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
1117.90759.6728590536990336.29
2125.567511.260635477788840.99
3131.532510.361153081670935.82
4143.60416666666712.687861384612942.57
5127.32583333333317.791179356040146.91

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 117.9075 & 9.67285905369903 & 36.29 \tabularnewline
2 & 125.5675 & 11.2606354777888 & 40.99 \tabularnewline
3 & 131.5325 & 10.3611530816709 & 35.82 \tabularnewline
4 & 143.604166666667 & 12.6878613846129 & 42.57 \tabularnewline
5 & 127.325833333333 & 17.7911793560401 & 46.91 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65309&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]117.9075[/C][C]9.67285905369903[/C][C]36.29[/C][/ROW]
[ROW][C]2[/C][C]125.5675[/C][C]11.2606354777888[/C][C]40.99[/C][/ROW]
[ROW][C]3[/C][C]131.5325[/C][C]10.3611530816709[/C][C]35.82[/C][/ROW]
[ROW][C]4[/C][C]143.604166666667[/C][C]12.6878613846129[/C][C]42.57[/C][/ROW]
[ROW][C]5[/C][C]127.325833333333[/C][C]17.7911793560401[/C][C]46.91[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65309&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65309&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
1117.90759.6728590536990336.29
2125.567511.260635477788840.99
3131.532510.361153081670935.82
4143.60416666666712.687861384612942.57
5127.32583333333317.791179356040146.91







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.59425235787943
beta0.0678121746522143
S.D.0.194150486375348
T-STAT0.349276357315501
p-value0.749960448047292

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.59425235787943 \tabularnewline
beta & 0.0678121746522143 \tabularnewline
S.D. & 0.194150486375348 \tabularnewline
T-STAT & 0.349276357315501 \tabularnewline
p-value & 0.749960448047292 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65309&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.59425235787943[/C][/ROW]
[ROW][C]beta[/C][C]0.0678121746522143[/C][/ROW]
[ROW][C]S.D.[/C][C]0.194150486375348[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.349276357315501[/C][/ROW]
[ROW][C]p-value[/C][C]0.749960448047292[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65309&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65309&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)
alpha3.59425235787943
beta0.0678121746522143
S.D.0.194150486375348
T-STAT0.349276357315501
p-value0.749960448047292







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.95784403991879
beta0.915271856963156
S.D.1.84350044421705
T-STAT0.496485834779323
p-value0.653651480816477
Lambda0.0847281430368435

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.95784403991879 \tabularnewline
beta & 0.915271856963156 \tabularnewline
S.D. & 1.84350044421705 \tabularnewline
T-STAT & 0.496485834779323 \tabularnewline
p-value & 0.653651480816477 \tabularnewline
Lambda & 0.0847281430368435 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65309&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.95784403991879[/C][/ROW]
[ROW][C]beta[/C][C]0.915271856963156[/C][/ROW]
[ROW][C]S.D.[/C][C]1.84350044421705[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.496485834779323[/C][/ROW]
[ROW][C]p-value[/C][C]0.653651480816477[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0847281430368435[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65309&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65309&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-1.95784403991879
beta0.915271856963156
S.D.1.84350044421705
T-STAT0.496485834779323
p-value0.653651480816477
Lambda0.0847281430368435



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')