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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 computationMon, 21 Dec 2009 08:15:49 -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/21/t1261408588yn5jedkc1bmha67.htm/, Retrieved Sun, 05 May 2024 15:45:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70248, Retrieved Sun, 05 May 2024 15:45:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

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...] [2008-12-14 11:22:46] [1dc7b54f2fa28720a65b8f3f53c2ed9f]
- RM D    [Standard Deviation-Mean Plot] [] [2009-12-21 15:15:49] [ce16745b5fa1a53fd3d9c8db848c7076] [Current]
- RM        [Variance Reduction Matrix] [] [2009-12-21 15:21:01] [8eb28aba8de3868ee2c810eecf1cb9a8]
- RMP         [(Partial) Autocorrelation Function] [] [2009-12-21 15:30:42] [8eb28aba8de3868ee2c810eecf1cb9a8]
- RMP         [(Partial) Autocorrelation Function] [] [2009-12-21 15:30:42] [34614c523ea6b7cb2b2f40e9d664a4b1]
- RMP         [(Partial) Autocorrelation Function] [] [2009-12-21 15:30:42] [34614c523ea6b7cb2b2f40e9d664a4b1]
- RMP         [(Partial) Autocorrelation Function] [] [2009-12-21 15:30:42] [8eb28aba8de3868ee2c810eecf1cb9a8]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70248&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]4 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=70248&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70248&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12554.44666666667190.570772791696571
23191.3225147.471609663753512.32
33902.32333333333218.664223632879720.77
44411.00833333333198.014401580626591.78

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2554.44666666667 & 190.570772791696 & 571 \tabularnewline
2 & 3191.3225 & 147.471609663753 & 512.32 \tabularnewline
3 & 3902.32333333333 & 218.664223632879 & 720.77 \tabularnewline
4 & 4411.00833333333 & 198.014401580626 & 591.78 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70248&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]2554.44666666667[/C][C]190.570772791696[/C][C]571[/C][/ROW]
[ROW][C]2[/C][C]3191.3225[/C][C]147.471609663753[/C][C]512.32[/C][/ROW]
[ROW][C]3[/C][C]3902.32333333333[/C][C]218.664223632879[/C][C]720.77[/C][/ROW]
[ROW][C]4[/C][C]4411.00833333333[/C][C]198.014401580626[/C][C]591.78[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70248&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70248&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
12554.44666666667190.570772791696571
23191.3225147.471609663753512.32
33902.32333333333218.664223632879720.77
44411.00833333333198.014401580626591.78






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha132.772463582960
beta0.0159065046896099
S.D.0.0234980000149642
T-STAT0.676930150628996
p-value0.568250135780154

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 132.772463582960 \tabularnewline
beta & 0.0159065046896099 \tabularnewline
S.D. & 0.0234980000149642 \tabularnewline
T-STAT & 0.676930150628996 \tabularnewline
p-value & 0.568250135780154 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70248&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]132.772463582960[/C][/ROW]
[ROW][C]beta[/C][C]0.0159065046896099[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0234980000149642[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.676930150628996[/C][/ROW]
[ROW][C]p-value[/C][C]0.568250135780154[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70248&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70248&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)
alpha132.772463582960
beta0.0159065046896099
S.D.0.0234980000149642
T-STAT0.676930150628996
p-value0.568250135780154






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.04412753925989
beta0.268397082287699
S.D.0.457914267030008
T-STAT0.586129547848551
p-value0.617125270347972
Lambda0.731602917712301

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.04412753925989 \tabularnewline
beta & 0.268397082287699 \tabularnewline
S.D. & 0.457914267030008 \tabularnewline
T-STAT & 0.586129547848551 \tabularnewline
p-value & 0.617125270347972 \tabularnewline
Lambda & 0.731602917712301 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70248&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.04412753925989[/C][/ROW]
[ROW][C]beta[/C][C]0.268397082287699[/C][/ROW]
[ROW][C]S.D.[/C][C]0.457914267030008[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.586129547848551[/C][/ROW]
[ROW][C]p-value[/C][C]0.617125270347972[/C][/ROW]
[ROW][C]Lambda[/C][C]0.731602917712301[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70248&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70248&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)
alpha3.04412753925989
beta0.268397082287699
S.D.0.457914267030008
T-STAT0.586129547848551
p-value0.617125270347972
Lambda0.731602917712301


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')