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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 computationWed, 29 Dec 2010 19:40:26 +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/29/t1293651672ssbed3ik2meca6e.htm/, Retrieved Fri, 03 May 2024 07:11:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=117064, Retrieved Fri, 03 May 2024 07:11:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102

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] [Standard Deviatio...] [2010-12-29 19:40:26] [76d5107cfd0c78d23318a36a1ce43bff] [Current]
- R P     [Standard Deviation-Mean Plot] [] [2011-12-21 20:56:01] [3931071255a6f7f4a767409781cc5f7d]
-   P       [Standard Deviation-Mean Plot] [] [2011-12-21 21:22:43] [3931071255a6f7f4a767409781cc5f7d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5.921
4.561
4.399
4.249
4.211
4.081
4.131
4.071
3.841
4.109
4.354
4.402
4.954
4.137
4.561
4.210
4.429
4.190
4.196
4.226
3.878
3.931
4.115
4.679
5.385
4.387
4.552
4.325
4.179
4.054
4.075
4.147
4.046
4.368
4.097
4.821
4.965
4.425
4.601
4.521
4.193
4.039
4.099
4.109
4.024
4.245
4.252
5.136
5.037
4.230
4.408
4.119
4.083
4.010
4.148
3.952
3.843
4.164
4.075
4.708

Tables (Output of Computation)





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=117064&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=117064&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117064&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.360833333333330.5275261016089992.08
24.292166666666670.311435629811.076
34.369666666666670.3956194988606951.339
44.384083333333330.3629807053057261.112
54.231416666666670.3378919833678251.194

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.36083333333333 & 0.527526101608999 & 2.08 \tabularnewline
2 & 4.29216666666667 & 0.31143562981 & 1.076 \tabularnewline
3 & 4.36966666666667 & 0.395619498860695 & 1.339 \tabularnewline
4 & 4.38408333333333 & 0.362980705305726 & 1.112 \tabularnewline
5 & 4.23141666666667 & 0.337891983367825 & 1.194 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117064&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]4.36083333333333[/C][C]0.527526101608999[/C][C]2.08[/C][/ROW]
[ROW][C]2[/C][C]4.29216666666667[/C][C]0.31143562981[/C][C]1.076[/C][/ROW]
[ROW][C]3[/C][C]4.36966666666667[/C][C]0.395619498860695[/C][C]1.339[/C][/ROW]
[ROW][C]4[/C][C]4.38408333333333[/C][C]0.362980705305726[/C][C]1.112[/C][/ROW]
[ROW][C]5[/C][C]4.23141666666667[/C][C]0.337891983367825[/C][C]1.194[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117064&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117064&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
14.360833333333330.5275261016089992.08
24.292166666666670.311435629811.076
34.369666666666670.3956194988606951.339
44.384083333333330.3629807053057261.112
54.231416666666670.3378919833678251.194






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.50569161968677
beta0.668444431554758
S.D.0.651731855698161
T-STAT1.02564333124195
p-value0.380534148502539

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.50569161968677 \tabularnewline
beta & 0.668444431554758 \tabularnewline
S.D. & 0.651731855698161 \tabularnewline
T-STAT & 1.02564333124195 \tabularnewline
p-value & 0.380534148502539 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117064&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.50569161968677[/C][/ROW]
[ROW][C]beta[/C][C]0.668444431554758[/C][/ROW]
[ROW][C]S.D.[/C][C]0.651731855698161[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.02564333124195[/C][/ROW]
[ROW][C]p-value[/C][C]0.380534148502539[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117064&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117064&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-2.50569161968677
beta0.668444431554758
S.D.0.651731855698161
T-STAT1.02564333124195
p-value0.380534148502539






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-11.7622916194231
beta7.3695719969796
S.D.6.58601822296687
T-STAT1.11897230579781
p-value0.344671242408598
Lambda-6.3695719969796

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -11.7622916194231 \tabularnewline
beta & 7.3695719969796 \tabularnewline
S.D. & 6.58601822296687 \tabularnewline
T-STAT & 1.11897230579781 \tabularnewline
p-value & 0.344671242408598 \tabularnewline
Lambda & -6.3695719969796 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117064&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-11.7622916194231[/C][/ROW]
[ROW][C]beta[/C][C]7.3695719969796[/C][/ROW]
[ROW][C]S.D.[/C][C]6.58601822296687[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11897230579781[/C][/ROW]
[ROW][C]p-value[/C][C]0.344671242408598[/C][/ROW]
[ROW][C]Lambda[/C][C]-6.3695719969796[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117064&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117064&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-11.7622916194231
beta7.3695719969796
S.D.6.58601822296687
T-STAT1.11897230579781
p-value0.344671242408598
Lambda-6.3695719969796


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 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')