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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 computationFri, 21 Apr 2017 15:12:36 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/21/t1492783978iudwsqpagw4ykdu.htm/, Retrieved Mon, 13 May 2024 05:44:16 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 13 May 2024 05:44:16 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
78,46
78,59
81,37
83,61
83,85
84,08
84,56
84,65
85,41
85,75
86,21
86,38
86,65
87,30
87,87
88,23
88,33
88,62
88,67
88,85
88,87
89,20
89,38
89,65
90,37
90,38
91,43
92,09
92,21
92,31
92,62
93,13
93,17
93,42
93,50
95,75
97,29
98,01
98,02
98,20
98,29
98,39
98,42
98,70
98,90
99,04
99,31
99,34
99,35
99,51
99,88
99,91
100,30
100,74
101,16
101,30
101,37
101,68
101,68
101,89
101,93
102,66
102,68
103,13
103,14
104,01
104,17
104,41
104,71
105,51
105,98
106,25

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
183.57666666666672.717657190681087.92
288.46833333333330.8654356058533683
392.53166666666671.468504702275775.38
498.49250.5984696392390422.05
5100.7308333333330.9066768326078942.54000000000001
6104.0483333333331.390080660402214.31999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 83.5766666666667 & 2.71765719068108 & 7.92 \tabularnewline
2 & 88.4683333333333 & 0.865435605853368 & 3 \tabularnewline
3 & 92.5316666666667 & 1.46850470227577 & 5.38 \tabularnewline
4 & 98.4925 & 0.598469639239042 & 2.05 \tabularnewline
5 & 100.730833333333 & 0.906676832607894 & 2.54000000000001 \tabularnewline
6 & 104.048333333333 & 1.39008066040221 & 4.31999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]83.5766666666667[/C][C]2.71765719068108[/C][C]7.92[/C][/ROW]
[ROW][C]2[/C][C]88.4683333333333[/C][C]0.865435605853368[/C][C]3[/C][/ROW]
[ROW][C]3[/C][C]92.5316666666667[/C][C]1.46850470227577[/C][C]5.38[/C][/ROW]
[ROW][C]4[/C][C]98.4925[/C][C]0.598469639239042[/C][C]2.05[/C][/ROW]
[ROW][C]5[/C][C]100.730833333333[/C][C]0.906676832607894[/C][C]2.54000000000001[/C][/ROW]
[ROW][C]6[/C][C]104.048333333333[/C][C]1.39008066040221[/C][C]4.31999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
183.57666666666672.717657190681087.92
288.46833333333330.8654356058533683
392.53166666666671.468504702275775.38
498.49250.5984696392390422.05
5100.7308333333330.9066768326078942.54000000000001
6104.0483333333331.390080660402214.31999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.78136639074313
beta-0.0576586595248134
S.D.0.0390535554195374
T-STAT-1.4763997517104
p-value0.213882781518315

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.78136639074313 \tabularnewline
beta & -0.0576586595248134 \tabularnewline
S.D. & 0.0390535554195374 \tabularnewline
T-STAT & -1.4763997517104 \tabularnewline
p-value & 0.213882781518315 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.78136639074313[/C][/ROW]
[ROW][C]beta[/C][C]-0.0576586595248134[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0390535554195374[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.4763997517104[/C][/ROW]
[ROW][C]p-value[/C][C]0.213882781518315[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha6.78136639074313
beta-0.0576586595248134
S.D.0.0390535554195374
T-STAT-1.4763997517104
p-value0.213882781518315






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha15.2403104408648
beta-3.31648040879518
S.D.2.69251666114044
T-STAT-1.23173997645402
p-value0.285506876413534
Lambda4.31648040879518

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 15.2403104408648 \tabularnewline
beta & -3.31648040879518 \tabularnewline
S.D. & 2.69251666114044 \tabularnewline
T-STAT & -1.23173997645402 \tabularnewline
p-value & 0.285506876413534 \tabularnewline
Lambda & 4.31648040879518 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15.2403104408648[/C][/ROW]
[ROW][C]beta[/C][C]-3.31648040879518[/C][/ROW]
[ROW][C]S.D.[/C][C]2.69251666114044[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.23173997645402[/C][/ROW]
[ROW][C]p-value[/C][C]0.285506876413534[/C][/ROW]
[ROW][C]Lambda[/C][C]4.31648040879518[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha15.2403104408648
beta-3.31648040879518
S.D.2.69251666114044
T-STAT-1.23173997645402
p-value0.285506876413534
Lambda4.31648040879518


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')