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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, 01 Dec 2009 04:59:25 -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/01/t1259668794ksp8ojc4exrdtlv.htm/, Retrieved Fri, 26 Apr 2024 04:03:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61996, Retrieved Fri, 26 Apr 2024 04:03:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
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]
-   PD        [Standard Deviation-Mean Plot] [] [2009-11-28 14:46:02] [74be16979710d4c4e7c6647856088456]
-   PD            [Standard Deviation-Mean Plot] [] [2009-12-01 11:59:25] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
6802.96
7132.68
7073.29
7264.5
7105.33
7218.71
7225.72
7354.25
7745.46
8070.26
8366.33
8667.51
8854.34
9218.1
9332.9
9358.31
9248.66
9401.2
9652.04
9957.38
10110.63
10169.26
10343.78
10750.21
11337.5
11786.96
12083.04
12007.74
11745.93
11051.51
11445.9
11924.88
12247.63
12690.91
12910.7
13202.12
13654.67
13862.82
13523.93
14211.17
14510.35
14289.23
14111.82
13086.59
13351.54
13747.69
12855.61
12926.93
12121.95
11731.65
11639.51
12163.78
12029.53
11234.18
9852.13
9709.04
9332.75
7108.6
6691.49
6143.05




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=61996&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=61996&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61996&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
17502.25579.0811742595491864.55
29699.73416666667561.3807330867891895.87
312036.235644.2395825453312150.61
413677.6958333333547.6352407057811654.74
59979.8052240.997346842376020.73

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7502.25 & 579.081174259549 & 1864.55 \tabularnewline
2 & 9699.73416666667 & 561.380733086789 & 1895.87 \tabularnewline
3 & 12036.235 & 644.239582545331 & 2150.61 \tabularnewline
4 & 13677.6958333333 & 547.635240705781 & 1654.74 \tabularnewline
5 & 9979.805 & 2240.99734684237 & 6020.73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61996&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]7502.25[/C][C]579.081174259549[/C][C]1864.55[/C][/ROW]
[ROW][C]2[/C][C]9699.73416666667[/C][C]561.380733086789[/C][C]1895.87[/C][/ROW]
[ROW][C]3[/C][C]12036.235[/C][C]644.239582545331[/C][C]2150.61[/C][/ROW]
[ROW][C]4[/C][C]13677.6958333333[/C][C]547.635240705781[/C][C]1654.74[/C][/ROW]
[ROW][C]5[/C][C]9979.805[/C][C]2240.99734684237[/C][C]6020.73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61996&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61996&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
17502.25579.0811742595491864.55
29699.73416666667561.3807330867891895.87
312036.235644.2395825453312150.61
413677.6958333333547.6352407057811654.74
59979.8052240.997346842376020.73







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1380.49276911192
beta-0.0440324806642163
S.D.0.179636723979713
T-STAT-0.245119592969136
p-value0.822174623467675

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1380.49276911192 \tabularnewline
beta & -0.0440324806642163 \tabularnewline
S.D. & 0.179636723979713 \tabularnewline
T-STAT & -0.245119592969136 \tabularnewline
p-value & 0.822174623467675 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61996&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1380.49276911192[/C][/ROW]
[ROW][C]beta[/C][C]-0.0440324806642163[/C][/ROW]
[ROW][C]S.D.[/C][C]0.179636723979713[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.245119592969136[/C][/ROW]
[ROW][C]p-value[/C][C]0.822174623467675[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61996&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61996&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)
alpha1380.49276911192
beta-0.0440324806642163
S.D.0.179636723979713
T-STAT-0.245119592969136
p-value0.822174623467675







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha8.77860513221234
beta-0.231727252237305
S.D.1.52304757650278
T-STAT-0.152147087072222
p-value0.888727264069616
Lambda1.23172725223731

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 8.77860513221234 \tabularnewline
beta & -0.231727252237305 \tabularnewline
S.D. & 1.52304757650278 \tabularnewline
T-STAT & -0.152147087072222 \tabularnewline
p-value & 0.888727264069616 \tabularnewline
Lambda & 1.23172725223731 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61996&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.77860513221234[/C][/ROW]
[ROW][C]beta[/C][C]-0.231727252237305[/C][/ROW]
[ROW][C]S.D.[/C][C]1.52304757650278[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.152147087072222[/C][/ROW]
[ROW][C]p-value[/C][C]0.888727264069616[/C][/ROW]
[ROW][C]Lambda[/C][C]1.23172725223731[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61996&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61996&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)
alpha8.77860513221234
beta-0.231727252237305
S.D.1.52304757650278
T-STAT-0.152147087072222
p-value0.888727264069616
Lambda1.23172725223731



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')