Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 15 Aug 2016 19:33:14 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/15/t1471286047sgkmsq6n7zd8ckb.htm/, Retrieved Sat, 27 Apr 2024 20:36:09 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 27 Apr 2024 20:36:09 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
21571,00
21493,00
21422,00
21272,00
22747,00
22676,00
21571,00
20831,00
20909,00
20909,00
20980,00
21130,00
21051,00
21643,00
21864,00
21643,00
22455,00
21935,00
20759,00
20467,00
20467,00
20610,00
20026,00
20467,00
20097,00
20467,00
21051,00
21272,00
21792,00
21571,00
20246,00
19726,00
19506,00
19726,00
19363,00
19506,00
19064,00
19805,00
20168,00
20246,00
21643,00
21643,00
19805,00
19363,00
19363,00
19584,00
18622,00
18180,00
17668,00
17817,00
18480,00
17960,00
19363,00
19584,00
18180,00
17668,00
17375,00
17668,00
16855,00
16563,00
15388,00
15680,00
15751,00
15830,00
17226,00
17076,00
15388,00
14647,00
14355,00
14725,00
13322,00
12367,00
10601,00
10750,00
10750,00
10601,00
11854,00
11926,00
10451,00
10159,00
9568,00
10380,00
8905,00
8022,00
6333,00
6697,00
6255,00
6404,00
7509,00
7730,00
6996,00
6917,00
6917,00
7879,00
6184,00
5079,00
3163,00
4709,00
4488,00
4566,00
6333,00
6112,00
5300,00
5671,00
5671,00
6996,00
5450,00
4566,00
3163,00
5008,00
4859,00
4930,00
6476,00
6333,00
5813,00
5892,00
6255,00
7067,00
5813,00
4787,00





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
121459.25642.4159124317011916
221115.5833333333763.8452316266612429
320360.25862.1609346709742429
419790.51049.197918758553463
517931.75889.6428420234923021
615146.251394.443657390424859
710330.58333333331101.81605941643904
86741.66666666667773.4585060661372800
95252.083333333331023.629234931313833
1055331042.562228358583904

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 21459.25 & 642.415912431701 & 1916 \tabularnewline
2 & 21115.5833333333 & 763.845231626661 & 2429 \tabularnewline
3 & 20360.25 & 862.160934670974 & 2429 \tabularnewline
4 & 19790.5 & 1049.19791875855 & 3463 \tabularnewline
5 & 17931.75 & 889.642842023492 & 3021 \tabularnewline
6 & 15146.25 & 1394.44365739042 & 4859 \tabularnewline
7 & 10330.5833333333 & 1101.8160594164 & 3904 \tabularnewline
8 & 6741.66666666667 & 773.458506066137 & 2800 \tabularnewline
9 & 5252.08333333333 & 1023.62923493131 & 3833 \tabularnewline
10 & 5533 & 1042.56222835858 & 3904 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]21459.25[/C][C]642.415912431701[/C][C]1916[/C][/ROW]
[ROW][C]2[/C][C]21115.5833333333[/C][C]763.845231626661[/C][C]2429[/C][/ROW]
[ROW][C]3[/C][C]20360.25[/C][C]862.160934670974[/C][C]2429[/C][/ROW]
[ROW][C]4[/C][C]19790.5[/C][C]1049.19791875855[/C][C]3463[/C][/ROW]
[ROW][C]5[/C][C]17931.75[/C][C]889.642842023492[/C][C]3021[/C][/ROW]
[ROW][C]6[/C][C]15146.25[/C][C]1394.44365739042[/C][C]4859[/C][/ROW]
[ROW][C]7[/C][C]10330.5833333333[/C][C]1101.8160594164[/C][C]3904[/C][/ROW]
[ROW][C]8[/C][C]6741.66666666667[/C][C]773.458506066137[/C][C]2800[/C][/ROW]
[ROW][C]9[/C][C]5252.08333333333[/C][C]1023.62923493131[/C][C]3833[/C][/ROW]
[ROW][C]10[/C][C]5533[/C][C]1042.56222835858[/C][C]3904[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
121459.25642.4159124317011916
221115.5833333333763.8452316266612429
320360.25862.1609346709742429
419790.51049.197918758553463
517931.75889.6428420234923021
615146.251394.443657390424859
710330.58333333331101.81605941643904
86741.66666666667773.4585060661372800
95252.083333333331023.629234931313833
1055331042.562228358583904







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1096.22241100992
beta-0.00987778455930086
S.D.0.0107060577779604
T-STAT-0.92263508792521
p-value0.383179968004858

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1096.22241100992 \tabularnewline
beta & -0.00987778455930086 \tabularnewline
S.D. & 0.0107060577779604 \tabularnewline
T-STAT & -0.92263508792521 \tabularnewline
p-value & 0.383179968004858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1096.22241100992[/C][/ROW]
[ROW][C]beta[/C][C]-0.00987778455930086[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0107060577779604[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.92263508792521[/C][/ROW]
[ROW][C]p-value[/C][C]0.383179968004858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha1096.22241100992
beta-0.00987778455930086
S.D.0.0107060577779604
T-STAT-0.92263508792521
p-value0.383179968004858







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.83381240370045
beta-0.105414016004749
S.D.0.130868795597244
T-STAT-0.805493895803599
p-value0.443814994120461
Lambda1.10541401600475

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.83381240370045 \tabularnewline
beta & -0.105414016004749 \tabularnewline
S.D. & 0.130868795597244 \tabularnewline
T-STAT & -0.805493895803599 \tabularnewline
p-value & 0.443814994120461 \tabularnewline
Lambda & 1.10541401600475 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.83381240370045[/C][/ROW]
[ROW][C]beta[/C][C]-0.105414016004749[/C][/ROW]
[ROW][C]S.D.[/C][C]0.130868795597244[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.805493895803599[/C][/ROW]
[ROW][C]p-value[/C][C]0.443814994120461[/C][/ROW]
[ROW][C]Lambda[/C][C]1.10541401600475[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha7.83381240370045
beta-0.105414016004749
S.D.0.130868795597244
T-STAT-0.805493895803599
p-value0.443814994120461
Lambda1.10541401600475



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')