Free Statistics

of Irreproducible Research!

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 computationWed, 16 Dec 2009 10:00:01 -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/16/t1260982830sx45kt94cnw6qsy.htm/, Retrieved Tue, 30 Apr 2024 08:45:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68480, Retrieved Tue, 30 Apr 2024 08:45:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
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] [] [2009-12-04 15:30:47] [897115520fe7b6114489bc0eeed64548]
-    D        [Standard Deviation-Mean Plot] [] [2009-12-16 17:00:01] [8cd69d0f4298074aa572ca2f9b39b6ae] [Current]
Feedback Forum

Post a new message
Dataseries X:
16,2
16,7
18,4
16
16,5
18,2
16,8
17,3
18
19,6
23,3
23,7
20,3
22,8
24,3
21,5
23,5
22,2
20,9
22,2
19,5
21,1
22
19,2
17,8
19,2
19,9
19,6
18,1
20,4
18,1
18,6
17,6
19,4
19,3
18,6
16,9
16,4
19
18,7
17,1
21,5
17,8
18,1
19
18,9
16,8
18,1
15,7
15,1
18,3
16,5
16,9
18,4
16,4
15,7
16,9
16,6
16,7
16,6




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=68480&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=68480&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68480&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
118.39166666666672.604352417617777.7
221.6251.532155344604465.1
318.88333333333330.8840334561062442.800
418.19166666666671.387907734248895.1
516.650.9634219315449583.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 18.3916666666667 & 2.60435241761777 & 7.7 \tabularnewline
2 & 21.625 & 1.53215534460446 & 5.1 \tabularnewline
3 & 18.8833333333333 & 0.884033456106244 & 2.800 \tabularnewline
4 & 18.1916666666667 & 1.38790773424889 & 5.1 \tabularnewline
5 & 16.65 & 0.963421931544958 & 3.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68480&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]18.3916666666667[/C][C]2.60435241761777[/C][C]7.7[/C][/ROW]
[ROW][C]2[/C][C]21.625[/C][C]1.53215534460446[/C][C]5.1[/C][/ROW]
[ROW][C]3[/C][C]18.8833333333333[/C][C]0.884033456106244[/C][C]2.800[/C][/ROW]
[ROW][C]4[/C][C]18.1916666666667[/C][C]1.38790773424889[/C][C]5.1[/C][/ROW]
[ROW][C]5[/C][C]16.65[/C][C]0.963421931544958[/C][C]3.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68480&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68480&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
118.39166666666672.604352417617777.7
221.6251.532155344604465.1
318.88333333333330.8840334561062442.800
418.19166666666671.387907734248895.1
516.650.9634219315449583.3







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.326969319253257
beta0.0612003657696438
S.D.0.216573542227641
T-STAT0.28258468296795
p-value0.795870639189817

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.326969319253257 \tabularnewline
beta & 0.0612003657696438 \tabularnewline
S.D. & 0.216573542227641 \tabularnewline
T-STAT & 0.28258468296795 \tabularnewline
p-value & 0.795870639189817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68480&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.326969319253257[/C][/ROW]
[ROW][C]beta[/C][C]0.0612003657696438[/C][/ROW]
[ROW][C]S.D.[/C][C]0.216573542227641[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.28258468296795[/C][/ROW]
[ROW][C]p-value[/C][C]0.795870639189817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68480&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68480&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)
alpha0.326969319253257
beta0.0612003657696438
S.D.0.216573542227641
T-STAT0.28258468296795
p-value0.795870639189817







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.11494063162093
beta1.17000522048075
S.D.2.54123155145266
T-STAT0.460408741506431
p-value0.676544043250362
Lambda-0.170005220480755

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.11494063162093 \tabularnewline
beta & 1.17000522048075 \tabularnewline
S.D. & 2.54123155145266 \tabularnewline
T-STAT & 0.460408741506431 \tabularnewline
p-value & 0.676544043250362 \tabularnewline
Lambda & -0.170005220480755 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68480&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.11494063162093[/C][/ROW]
[ROW][C]beta[/C][C]1.17000522048075[/C][/ROW]
[ROW][C]S.D.[/C][C]2.54123155145266[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.460408741506431[/C][/ROW]
[ROW][C]p-value[/C][C]0.676544043250362[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.170005220480755[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68480&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68480&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-3.11494063162093
beta1.17000522048075
S.D.2.54123155145266
T-STAT0.460408741506431
p-value0.676544043250362
Lambda-0.170005220480755



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')