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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 computationTue, 15 Nov 2016 13:49:44 +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/15/t14792177951qvs495m8hcixyu.htm/, Retrieved Mon, 06 May 2024 16:54:11 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 06 May 2024 16:54:11 +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 
95.97
96.22
95.8
96.02
96.04
96.15
96.15
95.99
96.08
96.29
96.3
96.44
96.44
96.83
96.7
97.06
97.64
97.61
97.61
97.61
97.55
97.58
97.79
97.79
97.79
97.79
98
98.37
98.68
98.89
98.89
98.89
98.88
98.97
99.05
99.05
99
99.03
99.2
100.3
100.79
100.75
100.75
100.17
99.98
99.93
100.04
100.04
100.49
100.71
100.7
101.27
101.07
101.17
100.71
100.59
100.52
100.65
100.62
100.62
100.59
100.42
100.55
100.41
100.4
99.93
100.26
100.34
100.24
99.98
100.08
100.24

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
196.12083333333330.1745882602183230.640000000000001
297.35083333333330.464375599024861.35000000000001
398.60416666666670.4865361489575281.25999999999999
499.99833333333330.6365651196186861.79000000000001
5100.760.2599999999999990.780000000000001
6100.2866666666670.2086899977275260.659999999999997

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 96.1208333333333 & 0.174588260218323 & 0.640000000000001 \tabularnewline
2 & 97.3508333333333 & 0.46437559902486 & 1.35000000000001 \tabularnewline
3 & 98.6041666666667 & 0.486536148957528 & 1.25999999999999 \tabularnewline
4 & 99.9983333333333 & 0.636565119618686 & 1.79000000000001 \tabularnewline
5 & 100.76 & 0.259999999999999 & 0.780000000000001 \tabularnewline
6 & 100.286666666667 & 0.208689997727526 & 0.659999999999997 \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]96.1208333333333[/C][C]0.174588260218323[/C][C]0.640000000000001[/C][/ROW]
[ROW][C]2[/C][C]97.3508333333333[/C][C]0.46437559902486[/C][C]1.35000000000001[/C][/ROW]
[ROW][C]3[/C][C]98.6041666666667[/C][C]0.486536148957528[/C][C]1.25999999999999[/C][/ROW]
[ROW][C]4[/C][C]99.9983333333333[/C][C]0.636565119618686[/C][C]1.79000000000001[/C][/ROW]
[ROW][C]5[/C][C]100.76[/C][C]0.259999999999999[/C][C]0.780000000000001[/C][/ROW]
[ROW][C]6[/C][C]100.286666666667[/C][C]0.208689997727526[/C][C]0.659999999999997[/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
196.12083333333330.1745882602183230.640000000000001
297.35083333333330.464375599024861.35000000000001
398.60416666666670.4865361489575281.25999999999999
499.99833333333330.6365651196186861.79000000000001
5100.760.2599999999999990.780000000000001
6100.2866666666670.2086899977275260.659999999999997






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.967282110731188
beta0.0135460556068829
S.D.0.0498331492873899
T-STAT0.271828206737692
p-value0.799207519762219

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.967282110731188 \tabularnewline
beta & 0.0135460556068829 \tabularnewline
S.D. & 0.0498331492873899 \tabularnewline
T-STAT & 0.271828206737692 \tabularnewline
p-value & 0.799207519762219 \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]-0.967282110731188[/C][/ROW]
[ROW][C]beta[/C][C]0.0135460556068829[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0498331492873899[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.271828206737692[/C][/ROW]
[ROW][C]p-value[/C][C]0.799207519762219[/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)
alpha-0.967282110731188
beta0.0135460556068829
S.D.0.0498331492873899
T-STAT0.271828206737692
p-value0.799207519762219






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-22.4757787076941
beta4.65354450781687
S.D.13.8747677770977
T-STAT0.335396208612459
p-value0.754179003813125
Lambda-3.65354450781687

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -22.4757787076941 \tabularnewline
beta & 4.65354450781687 \tabularnewline
S.D. & 13.8747677770977 \tabularnewline
T-STAT & 0.335396208612459 \tabularnewline
p-value & 0.754179003813125 \tabularnewline
Lambda & -3.65354450781687 \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]-22.4757787076941[/C][/ROW]
[ROW][C]beta[/C][C]4.65354450781687[/C][/ROW]
[ROW][C]S.D.[/C][C]13.8747677770977[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.335396208612459[/C][/ROW]
[ROW][C]p-value[/C][C]0.754179003813125[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.65354450781687[/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)
alpha-22.4757787076941
beta4.65354450781687
S.D.13.8747677770977
T-STAT0.335396208612459
p-value0.754179003813125
Lambda-3.65354450781687


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')