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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 computationMon, 21 Nov 2016 10:41:43 +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/21/t1479724958d4724vcqzvhgtnm.htm/, Retrieved Tue, 07 May 2024 01:32:21 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 07 May 2024 01:32:21 +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 
98.98
98.97
98.91
98.98
98.95
98.96
98.96
99.04
99.33
100.04
100.14
100.21
100.21
100.27
100.44
100.57
100.51
100.47
100.47
100.49
101
101.61
101.65
101.74
101.74
101.73
101.77
101.82
101.97
102.09
102.09
102.08
102.42
102.78
103.04
103.08
99.16
99.19
99.23
99.31
99.46
99.49
99.95
100.14
100.43
101.1
101.26
101.28
101.04
101.12
101.07
100.97
101.01
100.99
101.19
101.25
101.33
101.79
102.06
102.09
102.27
102.26
102.46
102.46
102.51
102.56
102.59
102.26
102.33
102.84
102.93
102.95

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.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]'Herman Ole Andreas Wold' @ wold.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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.28916666666670.519430778192181.3
2100.7858333333330.5648243223795491.53
3102.21750.4967553815419731.34999999999999
41000.8325972506669622.12
5101.3258333333330.4146511860113361.12
6102.5350.252316540012020.689999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.2891666666667 & 0.51943077819218 & 1.3 \tabularnewline
2 & 100.785833333333 & 0.564824322379549 & 1.53 \tabularnewline
3 & 102.2175 & 0.496755381541973 & 1.34999999999999 \tabularnewline
4 & 100 & 0.832597250666962 & 2.12 \tabularnewline
5 & 101.325833333333 & 0.414651186011336 & 1.12 \tabularnewline
6 & 102.535 & 0.25231654001202 & 0.689999999999998 \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]99.2891666666667[/C][C]0.51943077819218[/C][C]1.3[/C][/ROW]
[ROW][C]2[/C][C]100.785833333333[/C][C]0.564824322379549[/C][C]1.53[/C][/ROW]
[ROW][C]3[/C][C]102.2175[/C][C]0.496755381541973[/C][C]1.34999999999999[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]0.832597250666962[/C][C]2.12[/C][/ROW]
[ROW][C]5[/C][C]101.325833333333[/C][C]0.414651186011336[/C][C]1.12[/C][/ROW]
[ROW][C]6[/C][C]102.535[/C][C]0.25231654001202[/C][C]0.689999999999998[/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
199.28916666666670.519430778192181.3
2100.7858333333330.5648243223795491.53
3102.21750.4967553815419731.34999999999999
41000.8325972506669622.12
5101.3258333333330.4146511860113361.12
6102.5350.252316540012020.689999999999998






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha10.6463238915995
beta-0.100300311072215
S.D.0.0570840511425153
T-STAT-1.75706364675847
p-value0.153742870017485

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 10.6463238915995 \tabularnewline
beta & -0.100300311072215 \tabularnewline
S.D. & 0.0570840511425153 \tabularnewline
T-STAT & -1.75706364675847 \tabularnewline
p-value & 0.153742870017485 \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]10.6463238915995[/C][/ROW]
[ROW][C]beta[/C][C]-0.100300311072215[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0570840511425153[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.75706364675847[/C][/ROW]
[ROW][C]p-value[/C][C]0.153742870017485[/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)
alpha10.6463238915995
beta-0.100300311072215
S.D.0.0570840511425153
T-STAT-1.75706364675847
p-value0.153742870017485






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha99.9536719326898
beta-21.8146667960357
S.D.11.3814256045446
T-STAT-1.91669018926109
p-value0.1277574703208
Lambda22.8146667960357

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 99.9536719326898 \tabularnewline
beta & -21.8146667960357 \tabularnewline
S.D. & 11.3814256045446 \tabularnewline
T-STAT & -1.91669018926109 \tabularnewline
p-value & 0.1277574703208 \tabularnewline
Lambda & 22.8146667960357 \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]99.9536719326898[/C][/ROW]
[ROW][C]beta[/C][C]-21.8146667960357[/C][/ROW]
[ROW][C]S.D.[/C][C]11.3814256045446[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.91669018926109[/C][/ROW]
[ROW][C]p-value[/C][C]0.1277574703208[/C][/ROW]
[ROW][C]Lambda[/C][C]22.8146667960357[/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)
alpha99.9536719326898
beta-21.8146667960357
S.D.11.3814256045446
T-STAT-1.91669018926109
p-value0.1277574703208
Lambda22.8146667960357


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')