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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 computationSun, 27 Nov 2016 11:01:45 +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/2016/Nov/27/t14802445329oes0cu1w53ab3x.htm/, Retrieved Tue, 30 Apr 2024 00:43:31 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 30 Apr 2024 00:43:31 +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 
95.9
89.2
100.2
102.3
102.2
100.5
104.1
94.9
97.3
100.3
98
115.1
94.4
91.6
104.1
107.8
101.7
104.1
102
99.9
101.6
101.3
101
115.9
97.5
97.6
109.2
101.6
108.8
108.8
100.9
107.4
101.7
104.5
106.1
116.7
103.7
96.5
114.1
102.8
114.5
107.2
107.9
111.3
99.8
106.7
106.9
115.3
106.1
97.3
109
109.8
116.5
108.3
110.8
108.7
104
111.3
106.5
120.5
110
99.7
109
112.2
116
112.3
113.2
109.9
107.6
114.9
105.7
123.3

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
11006.2237083362369625.9
2102.1166666666676.0870702511490924.3
3105.0666666666675.5665124275492819.2
4107.2255.9160989911196818.8
5109.0666666666675.8367695506914423.2
6111.155.8211995015085723.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100 & 6.22370833623696 & 25.9 \tabularnewline
2 & 102.116666666667 & 6.08707025114909 & 24.3 \tabularnewline
3 & 105.066666666667 & 5.56651242754928 & 19.2 \tabularnewline
4 & 107.225 & 5.91609899111968 & 18.8 \tabularnewline
5 & 109.066666666667 & 5.83676955069144 & 23.2 \tabularnewline
6 & 111.15 & 5.82119950150857 & 23.6 \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]100[/C][C]6.22370833623696[/C][C]25.9[/C][/ROW]
[ROW][C]2[/C][C]102.116666666667[/C][C]6.08707025114909[/C][C]24.3[/C][/ROW]
[ROW][C]3[/C][C]105.066666666667[/C][C]5.56651242754928[/C][C]19.2[/C][/ROW]
[ROW][C]4[/C][C]107.225[/C][C]5.91609899111968[/C][C]18.8[/C][/ROW]
[ROW][C]5[/C][C]109.066666666667[/C][C]5.83676955069144[/C][C]23.2[/C][/ROW]
[ROW][C]6[/C][C]111.15[/C][C]5.82119950150857[/C][C]23.6[/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
11006.2237083362369625.9
2102.1166666666676.0870702511490924.3
3105.0666666666675.5665124275492819.2
4107.2255.9160989911196818.8
5109.0666666666675.8367695506914423.2
6111.155.8211995015085723.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha9.38306249675587
beta-0.0328493455541149
S.D.0.0215154942214268
T-STAT-1.52677624859767
p-value0.201524235903537

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 9.38306249675587 \tabularnewline
beta & -0.0328493455541149 \tabularnewline
S.D. & 0.0215154942214268 \tabularnewline
T-STAT & -1.52677624859767 \tabularnewline
p-value & 0.201524235903537 \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]9.38306249675587[/C][/ROW]
[ROW][C]beta[/C][C]-0.0328493455541149[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0215154942214268[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.52677624859767[/C][/ROW]
[ROW][C]p-value[/C][C]0.201524235903537[/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)
alpha9.38306249675587
beta-0.0328493455541149
S.D.0.0215154942214268
T-STAT-1.52677624859767
p-value0.201524235903537






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.48721040115758
beta-0.58177667870834
S.D.0.386958174184694
T-STAT-1.50346140105225
p-value0.207151090726428
Lambda1.58177667870834

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.48721040115758 \tabularnewline
beta & -0.58177667870834 \tabularnewline
S.D. & 0.386958174184694 \tabularnewline
T-STAT & -1.50346140105225 \tabularnewline
p-value & 0.207151090726428 \tabularnewline
Lambda & 1.58177667870834 \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]4.48721040115758[/C][/ROW]
[ROW][C]beta[/C][C]-0.58177667870834[/C][/ROW]
[ROW][C]S.D.[/C][C]0.386958174184694[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.50346140105225[/C][/ROW]
[ROW][C]p-value[/C][C]0.207151090726428[/C][/ROW]
[ROW][C]Lambda[/C][C]1.58177667870834[/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)
alpha4.48721040115758
beta-0.58177667870834
S.D.0.386958174184694
T-STAT-1.50346140105225
p-value0.207151090726428
Lambda1.58177667870834


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')