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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 16 Dec 2007 13:13:22 -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/Dec/16/t1197835025tb4zj9yy9wyg3lu.htm/, Retrieved Thu, 02 May 2024 04:40:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4252, Retrieved Thu, 02 May 2024 04:40:27 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2007-12-16 20:13:22] [ba3202e2798d2e4685d19d988e9c69df] [Current]
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Dataseries X:
92,81
59,04
72,81
91,81
68,07
49,16
124,61
109,89
110,51
114,77
92,37
103,63
90,43
65,86
83,33
94,49
68,98
55,46
132,89
121,71
127,01
134,04
106,48
117,55
101,61
82,66
89,28
109,24
88,16
59,23
164,21
125,13
152,68
132,96
112,42
136,43
107,32
87,61
97,86
106,60
92,17
65,31
161,49
162,25
175,13
147,28
144,48
122,67
102,27
88,64
89,59
112,20
91,98
57,85
160,49
128,33
140,69
126,61
129,27
124,27
112,90
92,54
85,70
116,72
92,08
58,98
154,50
145,55
146,60
143,51
113,52
104,80




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=4252&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=4252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4252&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
190.7923.789994459092234.18
299.852527.473119465794575
3112.83416666666730.787746221902091.4
4122.51416666666734.987899066114483.32
5112.682527.917682283651592.42
6113.9529.2820295496309105.34

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 90.79 & 23.7899944590922 & 34.18 \tabularnewline
2 & 99.8525 & 27.4731194657945 & 75 \tabularnewline
3 & 112.834166666667 & 30.7877462219020 & 91.4 \tabularnewline
4 & 122.514166666667 & 34.9878990661144 & 83.32 \tabularnewline
5 & 112.6825 & 27.9176822836515 & 92.42 \tabularnewline
6 & 113.95 & 29.2820295496309 & 105.34 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4252&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]90.79[/C][C]23.7899944590922[/C][C]34.18[/C][/ROW]
[ROW][C]2[/C][C]99.8525[/C][C]27.4731194657945[/C][C]75[/C][/ROW]
[ROW][C]3[/C][C]112.834166666667[/C][C]30.7877462219020[/C][C]91.4[/C][/ROW]
[ROW][C]4[/C][C]122.514166666667[/C][C]34.9878990661144[/C][C]83.32[/C][/ROW]
[ROW][C]5[/C][C]112.6825[/C][C]27.9176822836515[/C][C]92.42[/C][/ROW]
[ROW][C]6[/C][C]113.95[/C][C]29.2820295496309[/C][C]105.34[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4252&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
190.7923.789994459092234.18
299.852527.473119465794575
3112.83416666666730.787746221902091.4
4122.51416666666734.987899066114483.32
5112.682527.917682283651592.42
6113.9529.2820295496309105.34







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-3.41981049144058
beta0.298422266026083
S.D.0.0674903148528975
T-STAT4.42170505022131
p-value0.0114956796129894

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.41981049144058 \tabularnewline
beta & 0.298422266026083 \tabularnewline
S.D. & 0.0674903148528975 \tabularnewline
T-STAT & 4.42170505022131 \tabularnewline
p-value & 0.0114956796129894 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4252&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.41981049144058[/C][/ROW]
[ROW][C]beta[/C][C]0.298422266026083[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0674903148528975[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.42170505022131[/C][/ROW]
[ROW][C]p-value[/C][C]0.0114956796129894[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4252&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4252&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-3.41981049144058
beta0.298422266026083
S.D.0.0674903148528975
T-STAT4.42170505022131
p-value0.0114956796129894







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.73260216178033
beta1.08751345407908
S.D.0.233718407986533
T-STAT4.65309285412274
p-value0.0096391500310474
Lambda-0.0875134540790787

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.73260216178033 \tabularnewline
beta & 1.08751345407908 \tabularnewline
S.D. & 0.233718407986533 \tabularnewline
T-STAT & 4.65309285412274 \tabularnewline
p-value & 0.0096391500310474 \tabularnewline
Lambda & -0.0875134540790787 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4252&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.73260216178033[/C][/ROW]
[ROW][C]beta[/C][C]1.08751345407908[/C][/ROW]
[ROW][C]S.D.[/C][C]0.233718407986533[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.65309285412274[/C][/ROW]
[ROW][C]p-value[/C][C]0.0096391500310474[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0875134540790787[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4252&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4252&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-1.73260216178033
beta1.08751345407908
S.D.0.233718407986533
T-STAT4.65309285412274
p-value0.0096391500310474
Lambda-0.0875134540790787



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')