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Author's title

Standard deviation mean plot - Nieuwe geregistreerde domeinnamen - Dorien D...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 15 May 2009 12:10:29 -0600
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/May/15/t1242411083sbg82fsavfasqzz.htm/, Retrieved Thu, 31 Oct 2024 23:50:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40155, Retrieved Thu, 31 Oct 2024 23:50:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact207
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [bootstrap plot 50...] [2009-05-09 10:36:24] [74be16979710d4c4e7c6647856088456]
- RMP     [Standard Deviation-Mean Plot] [Standard deviatio...] [2009-05-15 18:10:29] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
8166
2322
2924
5209
5597
5616
5764
5854
6019
6047
6082
6251
6576
6820
7024
7102
7107
7237
7630
7842
8086
8201
8323
9016
9077
9115
9230
9535
9565
9807
9815
9999
10176
10416
10439
10737
10790
11196
11221
11340
11356
11772
11836
11926
12013
12132
12178
12382
12448
12543
12662
12692
12767
13136
13145
13330
13381
13533
14176
14314
14444
15092
15130
15550
15557
15874
15892
16364
16379
16668
16713
16830
17368
17808
17846
18137
18504
18898
18938
19139
19573
19796
19845
21461




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40155&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40155&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40155&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
15487.583333333331525.987576402035844
27580.33333333333725.608125309492440
39825.91666666667546.1635549795311660
411678.5486.8174008991281592
513177.25609.5588755216951866
615874.4166666667748.280751679032386
718942.751133.518987690354093

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5487.58333333333 & 1525.98757640203 & 5844 \tabularnewline
2 & 7580.33333333333 & 725.60812530949 & 2440 \tabularnewline
3 & 9825.91666666667 & 546.163554979531 & 1660 \tabularnewline
4 & 11678.5 & 486.817400899128 & 1592 \tabularnewline
5 & 13177.25 & 609.558875521695 & 1866 \tabularnewline
6 & 15874.4166666667 & 748.28075167903 & 2386 \tabularnewline
7 & 18942.75 & 1133.51898769035 & 4093 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40155&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]5487.58333333333[/C][C]1525.98757640203[/C][C]5844[/C][/ROW]
[ROW][C]2[/C][C]7580.33333333333[/C][C]725.60812530949[/C][C]2440[/C][/ROW]
[ROW][C]3[/C][C]9825.91666666667[/C][C]546.163554979531[/C][C]1660[/C][/ROW]
[ROW][C]4[/C][C]11678.5[/C][C]486.817400899128[/C][C]1592[/C][/ROW]
[ROW][C]5[/C][C]13177.25[/C][C]609.558875521695[/C][C]1866[/C][/ROW]
[ROW][C]6[/C][C]15874.4166666667[/C][C]748.28075167903[/C][C]2386[/C][/ROW]
[ROW][C]7[/C][C]18942.75[/C][C]1133.51898769035[/C][C]4093[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40155&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40155&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
15487.583333333331525.987576402035844
27580.33333333333725.608125309492440
39825.91666666667546.1635549795311660
411678.5486.8174008991281592
513177.25609.5588755216951866
615874.4166666667748.280751679032386
718942.751133.518987690354093







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha988.871302280462
beta-0.0138816635447318
S.D.0.0352765476795026
T-STAT-0.393509695757381
p-value0.710163071642617

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 988.871302280462 \tabularnewline
beta & -0.0138816635447318 \tabularnewline
S.D. & 0.0352765476795026 \tabularnewline
T-STAT & -0.393509695757381 \tabularnewline
p-value & 0.710163071642617 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40155&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]988.871302280462[/C][/ROW]
[ROW][C]beta[/C][C]-0.0138816635447318[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0352765476795026[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.393509695757381[/C][/ROW]
[ROW][C]p-value[/C][C]0.710163071642617[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40155&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40155&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)
alpha988.871302280462
beta-0.0138816635447318
S.D.0.0352765476795026
T-STAT-0.393509695757381
p-value0.710163071642617







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha9.04626818505778
beta-0.258825636444945
S.D.0.41110053756765
T-STAT-0.629592065182726
p-value0.556605795600512
Lambda1.25882563644495

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.04626818505778 \tabularnewline
beta & -0.258825636444945 \tabularnewline
S.D. & 0.41110053756765 \tabularnewline
T-STAT & -0.629592065182726 \tabularnewline
p-value & 0.556605795600512 \tabularnewline
Lambda & 1.25882563644495 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40155&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.04626818505778[/C][/ROW]
[ROW][C]beta[/C][C]-0.258825636444945[/C][/ROW]
[ROW][C]S.D.[/C][C]0.41110053756765[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.629592065182726[/C][/ROW]
[ROW][C]p-value[/C][C]0.556605795600512[/C][/ROW]
[ROW][C]Lambda[/C][C]1.25882563644495[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40155&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40155&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)
alpha9.04626818505778
beta-0.258825636444945
S.D.0.41110053756765
T-STAT-0.629592065182726
p-value0.556605795600512
Lambda1.25882563644495



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')