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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 20 Dec 2010 14:53:45 +0000
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/Dec/20/t1292856705i0mvy19nnv03b4m.htm/, Retrieved Fri, 03 May 2024 17:56:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112982, Retrieved Fri, 03 May 2024 17:56:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   PD    [Standard Deviation-Mean Plot] [test 4] [2010-12-05 10:51:45] [74be16979710d4c4e7c6647856088456]
-           [Standard Deviation-Mean Plot] [W9 - Blog 7] [2010-12-06 15:54:04] [1aa8d85d6b335d32b1f6be940e33a166]
-   PD          [Standard Deviation-Mean Plot] [SMP Likeur] [2010-12-20 14:53:45] [47bfda5353cd53c1cf7ea7aa9038654a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25,00
25,09
25,03
25,21
25,33
25,23
25,13
25,03
25,03
25,15
25,18
24,90
25,18
25,25
25,28
25,32
25,27
25,22
25,14
25,41
25,72
25,66
25,65
25,27
23,90
24,06
24,33
24,39
24,39
24,49
24,83
25,08
25,11
25,13
25,17
25,11
25,35
25,36
25,35
25,34
25,39
25,58
25,71
25,66
25,74
25,73
25,72
25,55
25,71
25,92
25,93
26,00
26,02
26,08
26,17
26,18
26,21
26,28
26,34
26,17
26,38
26,36
26,27
26,26
26,49
26,99
27,14
27,10
27,01
26,93
26,97
26,35
26,93

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=112982&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=112982&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112982&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
125.10916666666670.1188932548995360.43
225.36416666666670.2006108097030090.579999999999998
324.66583333333330.4584649948634591.27000000000000
425.540.1707203987385640.399999999999999
526.08416666666670.1772239637671310.629999999999999
626.68750.3593965902605490.879999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 25.1091666666667 & 0.118893254899536 & 0.43 \tabularnewline
2 & 25.3641666666667 & 0.200610809703009 & 0.579999999999998 \tabularnewline
3 & 24.6658333333333 & 0.458464994863459 & 1.27000000000000 \tabularnewline
4 & 25.54 & 0.170720398738564 & 0.399999999999999 \tabularnewline
5 & 26.0841666666667 & 0.177223963767131 & 0.629999999999999 \tabularnewline
6 & 26.6875 & 0.359396590260549 & 0.879999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112982&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]25.1091666666667[/C][C]0.118893254899536[/C][C]0.43[/C][/ROW]
[ROW][C]2[/C][C]25.3641666666667[/C][C]0.200610809703009[/C][C]0.579999999999998[/C][/ROW]
[ROW][C]3[/C][C]24.6658333333333[/C][C]0.458464994863459[/C][C]1.27000000000000[/C][/ROW]
[ROW][C]4[/C][C]25.54[/C][C]0.170720398738564[/C][C]0.399999999999999[/C][/ROW]
[ROW][C]5[/C][C]26.0841666666667[/C][C]0.177223963767131[/C][C]0.629999999999999[/C][/ROW]
[ROW][C]6[/C][C]26.6875[/C][C]0.359396590260549[/C][C]0.879999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112982&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112982&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
125.10916666666670.1188932548995360.43
225.36416666666670.2006108097030090.579999999999998
324.66583333333330.4584649948634591.27000000000000
425.540.1707203987385640.399999999999999
526.08416666666670.1772239637671310.629999999999999
626.68750.3593965902605490.879999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.550331876889264
beta-0.0118388490283207
S.D.0.0913035748174745
T-STAT-0.129664682374023
p-value0.90309062336875

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.550331876889264 \tabularnewline
beta & -0.0118388490283207 \tabularnewline
S.D. & 0.0913035748174745 \tabularnewline
T-STAT & -0.129664682374023 \tabularnewline
p-value & 0.90309062336875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112982&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.550331876889264[/C][/ROW]
[ROW][C]beta[/C][C]-0.0118388490283207[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0913035748174745[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.129664682374023[/C][/ROW]
[ROW][C]p-value[/C][C]0.90309062336875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112982&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112982&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)
alpha0.550331876889264
beta-0.0118388490283207
S.D.0.0913035748174745
T-STAT-0.129664682374023
p-value0.90309062336875






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.57149933246808
beta0.63718441479926
S.D.9.02270210339522
T-STAT0.0706201321397377
p-value0.947089859720052
Lambda0.36281558520074

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.57149933246808 \tabularnewline
beta & 0.63718441479926 \tabularnewline
S.D. & 9.02270210339522 \tabularnewline
T-STAT & 0.0706201321397377 \tabularnewline
p-value & 0.947089859720052 \tabularnewline
Lambda & 0.36281558520074 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112982&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.57149933246808[/C][/ROW]
[ROW][C]beta[/C][C]0.63718441479926[/C][/ROW]
[ROW][C]S.D.[/C][C]9.02270210339522[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0706201321397377[/C][/ROW]
[ROW][C]p-value[/C][C]0.947089859720052[/C][/ROW]
[ROW][C]Lambda[/C][C]0.36281558520074[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112982&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112982&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-3.57149933246808
beta0.63718441479926
S.D.9.02270210339522
T-STAT0.0706201321397377
p-value0.947089859720052
Lambda0.36281558520074


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')