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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 09 Dec 2012 10:59:10 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/09/t1355068769j2g6zwpv25xu30e.htm/, Retrieved Fri, 01 Nov 2024 00:18:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197949, Retrieved Fri, 01 Nov 2024 00:18:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [gemiddelde prijs ...] [2012-12-09 15:59:10] [725db2a88b228374c3964e39efbe73da] [Current]
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Dataseries X:
1,94
1,82
1,8
1,79
1,79
1,78
1,81
1,84
1,87
1,87
1,87
1,84
1,82
1,83
1,83
1,82
1,83
1,87
1,88
1,9
1,98
2,03
2,14
2,42
2,73
2,84
2,85
2,94
3,06
3,24
3,18
3,01
2,87
2,73
2,63
2,39
2,26
2,11
2,01
1,99
1,96
1,93
1,98
2,07
2,24
2,31
2,23
2,26
2,28
2,3
2,33
2,26
2,24
2,47
2,55
2,89
3,21
3,21
2,92
2,68
2,4
2,28
2,24
2,2
2,18
2,23
2,24
2,25
2,23
2,25
2,23
2,21




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197949&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197949&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197949&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' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.8350.04661252270288830.16
21.945833333333330.1796187038921020.6
32.87250.2377976603600790.85
42.11250.1394876990340660.38
52.611666666666670.3649865086755280.97
62.2450.05518563713009520.22

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.835 & 0.0466125227028883 & 0.16 \tabularnewline
2 & 1.94583333333333 & 0.179618703892102 & 0.6 \tabularnewline
3 & 2.8725 & 0.237797660360079 & 0.85 \tabularnewline
4 & 2.1125 & 0.139487699034066 & 0.38 \tabularnewline
5 & 2.61166666666667 & 0.364986508675528 & 0.97 \tabularnewline
6 & 2.245 & 0.0551856371300952 & 0.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197949&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]1.835[/C][C]0.0466125227028883[/C][C]0.16[/C][/ROW]
[ROW][C]2[/C][C]1.94583333333333[/C][C]0.179618703892102[/C][C]0.6[/C][/ROW]
[ROW][C]3[/C][C]2.8725[/C][C]0.237797660360079[/C][C]0.85[/C][/ROW]
[ROW][C]4[/C][C]2.1125[/C][C]0.139487699034066[/C][C]0.38[/C][/ROW]
[ROW][C]5[/C][C]2.61166666666667[/C][C]0.364986508675528[/C][C]0.97[/C][/ROW]
[ROW][C]6[/C][C]2.245[/C][C]0.0551856371300952[/C][C]0.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197949&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197949&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
11.8350.04661252270288830.16
21.945833333333330.1796187038921020.6
32.87250.2377976603600790.85
42.11250.1394876990340660.38
52.611666666666670.3649865086755280.97
62.2450.05518563713009520.22







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.299945873976044
beta0.207257403241037
S.D.0.108579652874017
T-STAT1.90880517440513
p-value0.128923317126287

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.299945873976044 \tabularnewline
beta & 0.207257403241037 \tabularnewline
S.D. & 0.108579652874017 \tabularnewline
T-STAT & 1.90880517440513 \tabularnewline
p-value & 0.128923317126287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197949&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.299945873976044[/C][/ROW]
[ROW][C]beta[/C][C]0.207257403241037[/C][/ROW]
[ROW][C]S.D.[/C][C]0.108579652874017[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.90880517440513[/C][/ROW]
[ROW][C]p-value[/C][C]0.128923317126287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197949&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197949&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-0.299945873976044
beta0.207257403241037
S.D.0.108579652874017
T-STAT1.90880517440513
p-value0.128923317126287







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.52586745937054
beta3.10896663245501
S.D.1.78290615720142
T-STAT1.74376347285438
p-value0.156149750346705
Lambda-2.10896663245501

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.52586745937054 \tabularnewline
beta & 3.10896663245501 \tabularnewline
S.D. & 1.78290615720142 \tabularnewline
T-STAT & 1.74376347285438 \tabularnewline
p-value & 0.156149750346705 \tabularnewline
Lambda & -2.10896663245501 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197949&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.52586745937054[/C][/ROW]
[ROW][C]beta[/C][C]3.10896663245501[/C][/ROW]
[ROW][C]S.D.[/C][C]1.78290615720142[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.74376347285438[/C][/ROW]
[ROW][C]p-value[/C][C]0.156149750346705[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.10896663245501[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197949&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197949&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-4.52586745937054
beta3.10896663245501
S.D.1.78290615720142
T-STAT1.74376347285438
p-value0.156149750346705
Lambda-2.10896663245501



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')