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Description of Statistical Computation

Author's title

Spreidings-en gemiddeldegrafieken Toegekende bouwvergunningen voor het aant...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 10 Jan 2010 10:57:16 -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/2010/Jan/10/t1263146337zmgg9klckj2hpcr.htm/, Retrieved Sun, 05 May 2024 07:20:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71830, Retrieved Sun, 05 May 2024 07:20:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W42
Estimated Impact159

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Spreidings-en gem...] [2010-01-10 17:57:16] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2766
3851
3289
3848
3348
3682
4058
3655
3811
3341
3032
3475
3353
3186
3902
4164
3499
4145
3796
3711
3949
3740
3243
4407
4814
3908
5250
3937
4004
5560
3922
3759
4138
4634
3996
4308
4143
4429
5219
4929
5761
5592
4163
4962
5208
4755
4491
5732
5731
5040
6102
4904
5369
5578
4619
4731
5011
5299
4146
4625
4736
4219
5116
4205
4121
5103
4300
4578
3809
5526
4248
3830
4430
4837
4408
4569
4104
4807
3944
3794
4390
4041
4104
4823

Tables (Output of Computation)





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=71830&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=71830&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71830&T=0

As an alternative you can also use a QR Code:  
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
13513376.4453358843631292
23757.91666666667383.8222738179581221
34352.5584.6611295131881801
44948.66666666667573.0034639484911618
55096.25547.3607959190091956
64482.58333333333538.8027904249361717
74354.25359.2087579920371043

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3513 & 376.445335884363 & 1292 \tabularnewline
2 & 3757.91666666667 & 383.822273817958 & 1221 \tabularnewline
3 & 4352.5 & 584.661129513188 & 1801 \tabularnewline
4 & 4948.66666666667 & 573.003463948491 & 1618 \tabularnewline
5 & 5096.25 & 547.360795919009 & 1956 \tabularnewline
6 & 4482.58333333333 & 538.802790424936 & 1717 \tabularnewline
7 & 4354.25 & 359.208757992037 & 1043 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71830&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]3513[/C][C]376.445335884363[/C][C]1292[/C][/ROW]
[ROW][C]2[/C][C]3757.91666666667[/C][C]383.822273817958[/C][C]1221[/C][/ROW]
[ROW][C]3[/C][C]4352.5[/C][C]584.661129513188[/C][C]1801[/C][/ROW]
[ROW][C]4[/C][C]4948.66666666667[/C][C]573.003463948491[/C][C]1618[/C][/ROW]
[ROW][C]5[/C][C]5096.25[/C][C]547.360795919009[/C][C]1956[/C][/ROW]
[ROW][C]6[/C][C]4482.58333333333[/C][C]538.802790424936[/C][C]1717[/C][/ROW]
[ROW][C]7[/C][C]4354.25[/C][C]359.208757992037[/C][C]1043[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71830&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71830&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13513376.4453358843631292
23757.91666666667383.8222738179581221
34352.5584.6611295131881801
44948.66666666667573.0034639484911618
55096.25547.3607959190091956
64482.58333333333538.8027904249361717
74354.25359.2087579920371043






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-84.3351105650477
beta0.129605924290049
S.D.0.0539262272555185
T-STAT2.40339313328814
p-value0.0613628906193826

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -84.3351105650477 \tabularnewline
beta & 0.129605924290049 \tabularnewline
S.D. & 0.0539262272555185 \tabularnewline
T-STAT & 2.40339313328814 \tabularnewline
p-value & 0.0613628906193826 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71830&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-84.3351105650477[/C][/ROW]
[ROW][C]beta[/C][C]0.129605924290049[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0539262272555185[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.40339313328814[/C][/ROW]
[ROW][C]p-value[/C][C]0.0613628906193826[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71830&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71830&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-84.3351105650477
beta0.129605924290049
S.D.0.0539262272555185
T-STAT2.40339313328814
p-value0.0613628906193826






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.8509987767402
beta1.19510296735332
S.D.0.496806620517507
T-STAT2.40556972873756
p-value0.0611980704189919
Lambda-0.195102967353321

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.8509987767402 \tabularnewline
beta & 1.19510296735332 \tabularnewline
S.D. & 0.496806620517507 \tabularnewline
T-STAT & 2.40556972873756 \tabularnewline
p-value & 0.0611980704189919 \tabularnewline
Lambda & -0.195102967353321 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71830&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.8509987767402[/C][/ROW]
[ROW][C]beta[/C][C]1.19510296735332[/C][/ROW]
[ROW][C]S.D.[/C][C]0.496806620517507[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.40556972873756[/C][/ROW]
[ROW][C]p-value[/C][C]0.0611980704189919[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.195102967353321[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71830&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71830&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.8509987767402
beta1.19510296735332
S.D.0.496806620517507
T-STAT2.40556972873756
p-value0.0611980704189919
Lambda-0.195102967353321


Figures (Output of Computation)

Input Parameters & R Code

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')