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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 computationThu, 28 Nov 2013 07:57:07 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/28/t1385643471qjous12k8xcrjrq.htm/, Retrieved Fri, 03 May 2024 05:27:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=229293, Retrieved Fri, 03 May 2024 05:27:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65

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] [] [2013-11-28 12:57:07] [a1de13929df8f72ca0bba4a56316571d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3.875
3.863
3.876
3.878
3.881
3.883
3.884
3.885
3.895
3.903
3.911
3.929
3.946
3.965
3.992
4.010
4.015
4.020
4.037
4.059
4.083
4.102
4.126
4.145
4.162
4.169
4.178
4.174
4.168
4.170
4.159
4.159
4.143
4.159
4.167
4.176
4.185
4.195
4.210
4.226
4.250
4.259
4.270
4.277
4.286
4.303
4.320
4.336
4.352
4.371
4.392
4.415
4.442
4.457
4.472
4.474
4.461
4.453
4.446
4.450
4.459
4.474
4.492
4.509
4.526
4.541
4.550
4.562
4.555
4.554
4.551
4.553

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'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229293&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229293&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229293&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'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13.888583333333330.01813313558270070.0659999999999998
24.041666666666670.06262490549197490.198999999999999
34.165333333333330.009651503258638890.0350000000000001
44.259750.04852014576909830.151000000000001
54.432083333333330.04034050149175210.122
64.527166666666670.03528799263549040.103000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3.88858333333333 & 0.0181331355827007 & 0.0659999999999998 \tabularnewline
2 & 4.04166666666667 & 0.0626249054919749 & 0.198999999999999 \tabularnewline
3 & 4.16533333333333 & 0.00965150325863889 & 0.0350000000000001 \tabularnewline
4 & 4.25975 & 0.0485201457690983 & 0.151000000000001 \tabularnewline
5 & 4.43208333333333 & 0.0403405014917521 & 0.122 \tabularnewline
6 & 4.52716666666667 & 0.0352879926354904 & 0.103000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229293&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]3.88858333333333[/C][C]0.0181331355827007[/C][C]0.0659999999999998[/C][/ROW]
[ROW][C]2[/C][C]4.04166666666667[/C][C]0.0626249054919749[/C][C]0.198999999999999[/C][/ROW]
[ROW][C]3[/C][C]4.16533333333333[/C][C]0.00965150325863889[/C][C]0.0350000000000001[/C][/ROW]
[ROW][C]4[/C][C]4.25975[/C][C]0.0485201457690983[/C][C]0.151000000000001[/C][/ROW]
[ROW][C]5[/C][C]4.43208333333333[/C][C]0.0403405014917521[/C][C]0.122[/C][/ROW]
[ROW][C]6[/C][C]4.52716666666667[/C][C]0.0352879926354904[/C][C]0.103000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229293&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229293&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
13.888583333333330.01813313558270070.0659999999999998
24.041666666666670.06262490549197490.198999999999999
34.165333333333330.009651503258638890.0350000000000001
44.259750.04852014576909830.151000000000001
54.432083333333330.04034050149175210.122
64.527166666666670.03528799263549040.103000000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0205651022995074
beta0.013349964863206
S.D.0.0402161328583802
T-STAT0.331955459522114
p-value0.756588385837677

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0205651022995074 \tabularnewline
beta & 0.013349964863206 \tabularnewline
S.D. & 0.0402161328583802 \tabularnewline
T-STAT & 0.331955459522114 \tabularnewline
p-value & 0.756588385837677 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229293&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0205651022995074[/C][/ROW]
[ROW][C]beta[/C][C]0.013349964863206[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0402161328583802[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.331955459522114[/C][/ROW]
[ROW][C]p-value[/C][C]0.756588385837677[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229293&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229293&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-0.0205651022995074
beta0.013349964863206
S.D.0.0402161328583802
T-STAT0.331955459522114
p-value0.756588385837677






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.37363870385269
beta3.38833113456632
S.D.5.89192039990884
T-STAT0.575080942135394
p-value0.596036543963904
Lambda-2.38833113456632

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -8.37363870385269 \tabularnewline
beta & 3.38833113456632 \tabularnewline
S.D. & 5.89192039990884 \tabularnewline
T-STAT & 0.575080942135394 \tabularnewline
p-value & 0.596036543963904 \tabularnewline
Lambda & -2.38833113456632 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229293&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.37363870385269[/C][/ROW]
[ROW][C]beta[/C][C]3.38833113456632[/C][/ROW]
[ROW][C]S.D.[/C][C]5.89192039990884[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.575080942135394[/C][/ROW]
[ROW][C]p-value[/C][C]0.596036543963904[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.38833113456632[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229293&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229293&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-8.37363870385269
beta3.38833113456632
S.D.5.89192039990884
T-STAT0.575080942135394
p-value0.596036543963904
Lambda-2.38833113456632


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')