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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 computationSun, 06 Dec 2009 13:04:16 -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/2009/Dec/06/t1260129887o2zjrov1dafhkzt.htm/, Retrieved Mon, 06 May 2024 03:10:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64493, Retrieved Mon, 06 May 2024 03:10:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155

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...] [2007-12-16 12:03:23] [0089dec2868056b990fdbd23bf9edb23]
- RM D    [Standard Deviation-Mean Plot] [PAPER] [2009-12-06 20:04:16] [2d9a0b3c2f25bb8f387fafb994d0d852] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.00
100.83
101.51
102.16
102.39
102.54
102.85
103.47
103.57
103.69
103.50
103.47
103.45
103.48
103.93
103.89
104.40
104.79
104.77
105.13
105.26
104.96
104.75
105.01
105.15
105.20
105.77
105.78
106.26
106.13
106.12
106.57
106.44
106.54
107.10
108.10
108.40
108.84
109.62
110.42
110.67
111.66
112.28
112.87
112.18
112.36
112.16
111.49
111.25
111.36
111.74
111.10
111.33
111.25
111.04
110.97
111.31
111.02
111.07
111.36

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64493&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]7 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=64493&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64493&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 time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1102.4983333333331.195201263639753.69
2104.4850.6405182560736544.43000000000001
3106.2633333333330.8068269312372346.58999999999999
4111.0791666666671.4801318020754610.71
5111.2333333333330.2134705997782769.35

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.498333333333 & 1.19520126363975 & 3.69 \tabularnewline
2 & 104.485 & 0.640518256073654 & 4.43000000000001 \tabularnewline
3 & 106.263333333333 & 0.806826931237234 & 6.58999999999999 \tabularnewline
4 & 111.079166666667 & 1.48013180207546 & 10.71 \tabularnewline
5 & 111.233333333333 & 0.213470599778276 & 9.35 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64493&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]102.498333333333[/C][C]1.19520126363975[/C][C]3.69[/C][/ROW]
[ROW][C]2[/C][C]104.485[/C][C]0.640518256073654[/C][C]4.43000000000001[/C][/ROW]
[ROW][C]3[/C][C]106.263333333333[/C][C]0.806826931237234[/C][C]6.58999999999999[/C][/ROW]
[ROW][C]4[/C][C]111.079166666667[/C][C]1.48013180207546[/C][C]10.71[/C][/ROW]
[ROW][C]5[/C][C]111.233333333333[/C][C]0.213470599778276[/C][C]9.35[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64493&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64493&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
1102.4983333333331.195201263639753.69
2104.4850.6405182560736544.43000000000001
3106.2633333333330.8068269312372346.58999999999999
4111.0791666666671.4801318020754610.71
5111.2333333333330.2134705997782769.35






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.82971254161590
beta-0.0183218110453563
S.D.0.0714906377095884
T-STAT-0.256282663469639
p-value0.814301966469959

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.82971254161590 \tabularnewline
beta & -0.0183218110453563 \tabularnewline
S.D. & 0.0714906377095884 \tabularnewline
T-STAT & -0.256282663469639 \tabularnewline
p-value & 0.814301966469959 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64493&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.82971254161590[/C][/ROW]
[ROW][C]beta[/C][C]-0.0183218110453563[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0714906377095884[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.256282663469639[/C][/ROW]
[ROW][C]p-value[/C][C]0.814301966469959[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64493&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64493&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)
alpha2.82971254161590
beta-0.0183218110453563
S.D.0.0714906377095884
T-STAT-0.256282663469639
p-value0.814301966469959






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha34.5192884298766
beta-7.45635877403739
S.D.11.0986265305154
T-STAT-0.671827162895906
p-value0.549802368388941
Lambda8.45635877403739

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 34.5192884298766 \tabularnewline
beta & -7.45635877403739 \tabularnewline
S.D. & 11.0986265305154 \tabularnewline
T-STAT & -0.671827162895906 \tabularnewline
p-value & 0.549802368388941 \tabularnewline
Lambda & 8.45635877403739 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64493&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]34.5192884298766[/C][/ROW]
[ROW][C]beta[/C][C]-7.45635877403739[/C][/ROW]
[ROW][C]S.D.[/C][C]11.0986265305154[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.671827162895906[/C][/ROW]
[ROW][C]p-value[/C][C]0.549802368388941[/C][/ROW]
[ROW][C]Lambda[/C][C]8.45635877403739[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64493&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64493&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)
alpha34.5192884298766
beta-7.45635877403739
S.D.11.0986265305154
T-STAT-0.671827162895906
p-value0.549802368388941
Lambda8.45635877403739


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')