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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 15:12:38 +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/t149278418474n5qb1agt2259z.htm/, Retrieved Mon, 13 May 2024 04:42:52 +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 04:42:52 +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 
100.18
99.73
99.69
99.45
99.47
99.56
99.54
99.87
99.73
99.86
99.91
99.91
99.91
99.87
99.77
100.14
100.04
100.11
100.13
100.22
100.59
100.25
99.94
99.85
99.85
99.85
100.15
100.34
100.72
100.61
100.61
100.52
100.64
100.57
100.16
100.2
100.2
99.99
99.69
99.85
99.54
99.67
99.72
99.74
99.97
100.29
100.57
100.77
100.3
100.32
100.32
100.37
100.47
100.68
100.7
100.62
100.52
100.62
100.52
100.57
100.59
100.59
100.56
100.44
100.39
100.51
100.4
100.45
100.42
100.38
100.25
100.34

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=&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=&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.74166666666670.2163260726241050.730000000000004
2100.0683333333330.2250589148456820.820000000000007
3100.3516666666670.3063222703842050.870000000000005
41000.3847076812334261.22999999999999
5100.5008333333330.1444398794927480.400000000000006
6100.4433333333330.1037771505182970.340000000000003

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.7416666666667 & 0.216326072624105 & 0.730000000000004 \tabularnewline
2 & 100.068333333333 & 0.225058914845682 & 0.820000000000007 \tabularnewline
3 & 100.351666666667 & 0.306322270384205 & 0.870000000000005 \tabularnewline
4 & 100 & 0.384707681233426 & 1.22999999999999 \tabularnewline
5 & 100.500833333333 & 0.144439879492748 & 0.400000000000006 \tabularnewline
6 & 100.443333333333 & 0.103777150518297 & 0.340000000000003 \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]99.7416666666667[/C][C]0.216326072624105[/C][C]0.730000000000004[/C][/ROW]
[ROW][C]2[/C][C]100.068333333333[/C][C]0.225058914845682[/C][C]0.820000000000007[/C][/ROW]
[ROW][C]3[/C][C]100.351666666667[/C][C]0.306322270384205[/C][C]0.870000000000005[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]0.384707681233426[/C][C]1.22999999999999[/C][/ROW]
[ROW][C]5[/C][C]100.500833333333[/C][C]0.144439879492748[/C][C]0.400000000000006[/C][/ROW]
[ROW][C]6[/C][C]100.443333333333[/C][C]0.103777150518297[/C][C]0.340000000000003[/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
199.74166666666670.2163260726241050.730000000000004
2100.0683333333330.2250589148456820.820000000000007
3100.3516666666670.3063222703842050.870000000000005
41000.3847076812334261.22999999999999
5100.5008333333330.1444398794927480.400000000000006
6100.4433333333330.1037771505182970.340000000000003






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha15.9647537252477
beta-0.157057019158946
S.D.0.155459232701666
T-STAT-1.01027784860064
p-value0.369511072709113

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 15.9647537252477 \tabularnewline
beta & -0.157057019158946 \tabularnewline
S.D. & 0.155459232701666 \tabularnewline
T-STAT & -1.01027784860064 \tabularnewline
p-value & 0.369511072709113 \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]15.9647537252477[/C][/ROW]
[ROW][C]beta[/C][C]-0.157057019158946[/C][/ROW]
[ROW][C]S.D.[/C][C]0.155459232701666[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.01027784860064[/C][/ROW]
[ROW][C]p-value[/C][C]0.369511072709113[/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)
alpha15.9647537252477
beta-0.157057019158946
S.D.0.155459232701666
T-STAT-1.01027784860064
p-value0.369511072709113






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha387.779162649205
beta-84.5102424397896
S.D.69.2519915985051
T-STAT-1.22032941564693
p-value0.289361567876457
Lambda85.5102424397896

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 387.779162649205 \tabularnewline
beta & -84.5102424397896 \tabularnewline
S.D. & 69.2519915985051 \tabularnewline
T-STAT & -1.22032941564693 \tabularnewline
p-value & 0.289361567876457 \tabularnewline
Lambda & 85.5102424397896 \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]387.779162649205[/C][/ROW]
[ROW][C]beta[/C][C]-84.5102424397896[/C][/ROW]
[ROW][C]S.D.[/C][C]69.2519915985051[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.22032941564693[/C][/ROW]
[ROW][C]p-value[/C][C]0.289361567876457[/C][/ROW]
[ROW][C]Lambda[/C][C]85.5102424397896[/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)
alpha387.779162649205
beta-84.5102424397896
S.D.69.2519915985051
T-STAT-1.22032941564693
p-value0.289361567876457
Lambda85.5102424397896


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')