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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 28 Nov 2007 06:14:41 -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/2007/Nov/28/t119625549828arek127i4ls05.htm/, Retrieved Thu, 02 May 2024 03:44:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7049, Retrieved Thu, 02 May 2024 03:44:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKlaas Van Pelt
Estimated Impact193

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] [SMP 1] [2007-11-28 13:14:41] [6abd901c2e17b7d5559c695bbff3d863] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7049&T=0

[TABLE]
[ROW][C]Summary of compuational 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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7049&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
126911.91666666676314.137376602299673
2256538306.2242051039411254
323293.16666666674863.977250868852418
423712.256639.8206865848410333
522142.255608.358504378657346
622916.16666666677303.0689045251710815

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 26911.9166666667 & 6314.13737660229 & 9673 \tabularnewline
2 & 25653 & 8306.22420510394 & 11254 \tabularnewline
3 & 23293.1666666667 & 4863.97725086885 & 2418 \tabularnewline
4 & 23712.25 & 6639.82068658484 & 10333 \tabularnewline
5 & 22142.25 & 5608.35850437865 & 7346 \tabularnewline
6 & 22916.1666666667 & 7303.06890452517 & 10815 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7049&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]26911.9166666667[/C][C]6314.13737660229[/C][C]9673[/C][/ROW]
[ROW][C]2[/C][C]25653[/C][C]8306.22420510394[/C][C]11254[/C][/ROW]
[ROW][C]3[/C][C]23293.1666666667[/C][C]4863.97725086885[/C][C]2418[/C][/ROW]
[ROW][C]4[/C][C]23712.25[/C][C]6639.82068658484[/C][C]10333[/C][/ROW]
[ROW][C]5[/C][C]22142.25[/C][C]5608.35850437865[/C][C]7346[/C][/ROW]
[ROW][C]6[/C][C]22916.1666666667[/C][C]7303.06890452517[/C][C]10815[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7049&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
126911.91666666676314.137376602299673
2256538306.2242051039411254
323293.16666666674863.977250868852418
423712.256639.8206865848410333
522142.255608.358504378657346
622916.16666666677303.0689045251710815






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha104.724364441318
beta0.265557440975019
S.D.0.309827710568145
T-STAT0.857113266234498
p-value0.439698315802258

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 104.724364441318 \tabularnewline
beta & 0.265557440975019 \tabularnewline
S.D. & 0.309827710568145 \tabularnewline
T-STAT & 0.857113266234498 \tabularnewline
p-value & 0.439698315802258 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7049&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]104.724364441318[/C][/ROW]
[ROW][C]beta[/C][C]0.265557440975019[/C][/ROW]
[ROW][C]S.D.[/C][C]0.309827710568145[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.857113266234498[/C][/ROW]
[ROW][C]p-value[/C][C]0.439698315802258[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7049&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7049&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)
alpha104.724364441318
beta0.265557440975019
S.D.0.309827710568145
T-STAT0.857113266234498
p-value0.439698315802258






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.65871505189988
beta1.03335471631399
S.D.1.17684805854510
T-STAT0.878069780385664
p-value0.429484765027775
Lambda-0.0333547163139865

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.65871505189988 \tabularnewline
beta & 1.03335471631399 \tabularnewline
S.D. & 1.17684805854510 \tabularnewline
T-STAT & 0.878069780385664 \tabularnewline
p-value & 0.429484765027775 \tabularnewline
Lambda & -0.0333547163139865 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7049&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.65871505189988[/C][/ROW]
[ROW][C]beta[/C][C]1.03335471631399[/C][/ROW]
[ROW][C]S.D.[/C][C]1.17684805854510[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.878069780385664[/C][/ROW]
[ROW][C]p-value[/C][C]0.429484765027775[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0333547163139865[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7049&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7049&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-1.65871505189988
beta1.03335471631399
S.D.1.17684805854510
T-STAT0.878069780385664
p-value0.429484765027775
Lambda-0.0333547163139865


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')