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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 computationSun, 14 Dec 2008 11:42:41 -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/2008/Dec/14/t1229280206ixjei7x9p3u038z.htm/, Retrieved Fri, 01 Nov 2024 00:11:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33533, Retrieved Fri, 01 Nov 2024 00:11:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact219

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] [mean plot bel20] [2008-12-10 18:16:19] [74be16979710d4c4e7c6647856088456]
-    D    [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-14 18:42:41] [c8dc05b1cdf5010d9a4f2d773adefb82] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9005,73
9018,68
9349,44
9327,78
9753,63
10443,5
10853,87
10704,02
11052,23
10935,47
10714,03
10394,48
10817,9
11251,2
11281,26
10539,68
10483,39
10947,43
10580,27
10582,92
10654,41
11014,51
10967,87
10433,56
10665,78
10666,71
10682,74
10777,22
10052,6
10213,97
10546,82
10767,2
10444,5
10314,68
9042,56
9220,75
9721,84
9978,53
9923,81
9892,56
10500,98
10179,35
10080,48
9492,44
8616,49
8685,4
8160,67
8048,1
8641,21
8526,63
8474,21
7916,13
7977,64
8334,59
8623,36
9098,03
9154,34
9284,73
9492,49
9682,35
9762,12
10124,63
10540,05
10601,61
10323,73
10418,4
10092,96
10364,91
10152,09
10032,8
10204,59
10001,6
10411,75
10673,38
10539,51
10723,78
10682,06
10283,19
10377,18
10486,64
10545,38
10554,27
10532,54
10324,31
10695,25
10827,81
10872,48
10971,19
11145,65
11234,68
11333,88
10997,97
11036,89
11257,35
11533,59
11963,12
12185,15
12377,62
12512,89
12631,48
12268,53
12754,8
13407,75
13480,21
13673,28
13239,71
13557,69
13901,28
13200,58
13406,97
12538,12
12419,57
12193,88
12656,63
12812,48
12056,67
11322,38
11530,75
11114,08
9181,73
8614,55

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'George Udny Yule' @ 72.249.76.132

\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' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33533&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33533&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33533&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110129.405783.6740938043062046.5
210796.2293.901398895493847.7
310282.9608333333584.1739787466551734.66
49440.05416666667837.4893913516252452.88
58767.1425572.5433907832191766.22
610218.2908333333241.515075699534839.49
710511.1658333333141.529685961403440.59
811155.8216666667345.8751141888521267.87
912999.1991666667606.8200690253821716.13
1012036.15333333331144.545816679614225.24

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10129.405 & 783.674093804306 & 2046.5 \tabularnewline
2 & 10796.2 & 293.901398895493 & 847.7 \tabularnewline
3 & 10282.9608333333 & 584.173978746655 & 1734.66 \tabularnewline
4 & 9440.05416666667 & 837.489391351625 & 2452.88 \tabularnewline
5 & 8767.1425 & 572.543390783219 & 1766.22 \tabularnewline
6 & 10218.2908333333 & 241.515075699534 & 839.49 \tabularnewline
7 & 10511.1658333333 & 141.529685961403 & 440.59 \tabularnewline
8 & 11155.8216666667 & 345.875114188852 & 1267.87 \tabularnewline
9 & 12999.1991666667 & 606.820069025382 & 1716.13 \tabularnewline
10 & 12036.1533333333 & 1144.54581667961 & 4225.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33533&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]10129.405[/C][C]783.674093804306[/C][C]2046.5[/C][/ROW]
[ROW][C]2[/C][C]10796.2[/C][C]293.901398895493[/C][C]847.7[/C][/ROW]
[ROW][C]3[/C][C]10282.9608333333[/C][C]584.173978746655[/C][C]1734.66[/C][/ROW]
[ROW][C]4[/C][C]9440.05416666667[/C][C]837.489391351625[/C][C]2452.88[/C][/ROW]
[ROW][C]5[/C][C]8767.1425[/C][C]572.543390783219[/C][C]1766.22[/C][/ROW]
[ROW][C]6[/C][C]10218.2908333333[/C][C]241.515075699534[/C][C]839.49[/C][/ROW]
[ROW][C]7[/C][C]10511.1658333333[/C][C]141.529685961403[/C][C]440.59[/C][/ROW]
[ROW][C]8[/C][C]11155.8216666667[/C][C]345.875114188852[/C][C]1267.87[/C][/ROW]
[ROW][C]9[/C][C]12999.1991666667[/C][C]606.820069025382[/C][C]1716.13[/C][/ROW]
[ROW][C]10[/C][C]12036.1533333333[/C][C]1144.54581667961[/C][C]4225.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33533&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33533&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
110129.405783.6740938043062046.5
210796.2293.901398895493847.7
310282.9608333333584.1739787466551734.66
49440.05416666667837.4893913516252452.88
58767.1425572.5433907832191766.22
610218.2908333333241.515075699534839.49
710511.1658333333141.529685961403440.59
811155.8216666667345.8751141888521267.87
912999.1991666667606.8200690253821716.13
1012036.15333333331144.545816679614225.24






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha169.919792392197
beta0.0362328453169978
S.D.0.0891107084506889
T-STAT0.406604839608564
p-value0.6949586777025

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 169.919792392197 \tabularnewline
beta & 0.0362328453169978 \tabularnewline
S.D. & 0.0891107084506889 \tabularnewline
T-STAT & 0.406604839608564 \tabularnewline
p-value & 0.6949586777025 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33533&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]169.919792392197[/C][/ROW]
[ROW][C]beta[/C][C]0.0362328453169978[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0891107084506889[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.406604839608564[/C][/ROW]
[ROW][C]p-value[/C][C]0.6949586777025[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33533&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33533&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)
alpha169.919792392197
beta0.0362328453169978
S.D.0.0891107084506889
T-STAT0.406604839608564
p-value0.6949586777025






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.81700201938225
beta0.360073564121071
S.D.2.01559130372558
T-STAT0.17864413458002
p-value0.862658310910488
Lambda0.639926435878929

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.81700201938225 \tabularnewline
beta & 0.360073564121071 \tabularnewline
S.D. & 2.01559130372558 \tabularnewline
T-STAT & 0.17864413458002 \tabularnewline
p-value & 0.862658310910488 \tabularnewline
Lambda & 0.639926435878929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33533&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.81700201938225[/C][/ROW]
[ROW][C]beta[/C][C]0.360073564121071[/C][/ROW]
[ROW][C]S.D.[/C][C]2.01559130372558[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.17864413458002[/C][/ROW]
[ROW][C]p-value[/C][C]0.862658310910488[/C][/ROW]
[ROW][C]Lambda[/C][C]0.639926435878929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33533&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33533&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)
alpha2.81700201938225
beta0.360073564121071
S.D.2.01559130372558
T-STAT0.17864413458002
p-value0.862658310910488
Lambda0.639926435878929


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')