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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, 25 Apr 2017 19:07:56 +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/25/t1493143690x20gznzq1678lby.htm/, Retrieved Sat, 11 May 2024 08:11:15 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 11 May 2024 08:11:15 +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 
94
94.45
94.34
94.39
94.68
94.76
94.96
95.01
95.1
95.23
95.26
95.34
95.71
96.07
96.19
96.11
96.31
96.46
96.68
96.69
96.72
96.92
97.04
97.18
97.83
98.25
98.24
98.28
98.53
98.62
98.84
98.94
98.94
99.1
99.15
99.26
99.01
99.43
99.62
99.43
99.81
99.99
100.24
100.32
100.32
100.47
100.62
100.72
100.92
101.13
101.26
101.36
101.52
101.59
101.86
101.74
101.78
101.9
101.83
101.98
102.19
102.59
102.35
102.67
102.61
102.93
103.12
103.2
103.05
103.45
103.66
103.74

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 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]5 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 time5 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
194.79333333333330.4269837836676611.34
296.50666666666670.441244795659931.47000000000001
398.6650.4450638360750281.43000000000001
499.99833333333330.5390704682107581.70999999999999
5101.57250.3385564274171371.06
6102.9633333333330.4990050707217921.55

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 94.7933333333333 & 0.426983783667661 & 1.34 \tabularnewline
2 & 96.5066666666667 & 0.44124479565993 & 1.47000000000001 \tabularnewline
3 & 98.665 & 0.445063836075028 & 1.43000000000001 \tabularnewline
4 & 99.9983333333333 & 0.539070468210758 & 1.70999999999999 \tabularnewline
5 & 101.5725 & 0.338556427417137 & 1.06 \tabularnewline
6 & 102.963333333333 & 0.499005070721792 & 1.55 \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]94.7933333333333[/C][C]0.426983783667661[/C][C]1.34[/C][/ROW]
[ROW][C]2[/C][C]96.5066666666667[/C][C]0.44124479565993[/C][C]1.47000000000001[/C][/ROW]
[ROW][C]3[/C][C]98.665[/C][C]0.445063836075028[/C][C]1.43000000000001[/C][/ROW]
[ROW][C]4[/C][C]99.9983333333333[/C][C]0.539070468210758[/C][C]1.70999999999999[/C][/ROW]
[ROW][C]5[/C][C]101.5725[/C][C]0.338556427417137[/C][C]1.06[/C][/ROW]
[ROW][C]6[/C][C]102.963333333333[/C][C]0.499005070721792[/C][C]1.55[/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
194.79333333333330.4269837836676611.34
296.50666666666670.441244795659931.47000000000001
398.6650.4450638360750281.43000000000001
499.99833333333330.5390704682107581.70999999999999
5101.57250.3385564274171371.06
6102.9633333333330.4990050707217921.55






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.202005230505258
beta0.00248594629157724
S.D.0.0110431933576934
T-STAT0.225111180349421
p-value0.832925646922036

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.202005230505258 \tabularnewline
beta & 0.00248594629157724 \tabularnewline
S.D. & 0.0110431933576934 \tabularnewline
T-STAT & 0.225111180349421 \tabularnewline
p-value & 0.832925646922036 \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]0.202005230505258[/C][/ROW]
[ROW][C]beta[/C][C]0.00248594629157724[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0110431933576934[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.225111180349421[/C][/ROW]
[ROW][C]p-value[/C][C]0.832925646922036[/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)
alpha0.202005230505258
beta0.00248594629157724
S.D.0.0110431933576934
T-STAT0.225111180349421
p-value0.832925646922036






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.1635601895501
beta0.2939994268279
S.D.2.54906133843795
T-STAT0.115336348480363
p-value0.913736632427088
Lambda0.7060005731721

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.1635601895501 \tabularnewline
beta & 0.2939994268279 \tabularnewline
S.D. & 2.54906133843795 \tabularnewline
T-STAT & 0.115336348480363 \tabularnewline
p-value & 0.913736632427088 \tabularnewline
Lambda & 0.7060005731721 \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]-2.1635601895501[/C][/ROW]
[ROW][C]beta[/C][C]0.2939994268279[/C][/ROW]
[ROW][C]S.D.[/C][C]2.54906133843795[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.115336348480363[/C][/ROW]
[ROW][C]p-value[/C][C]0.913736632427088[/C][/ROW]
[ROW][C]Lambda[/C][C]0.7060005731721[/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-2.1635601895501
beta0.2939994268279
S.D.2.54906133843795
T-STAT0.115336348480363
p-value0.913736632427088
Lambda0.7060005731721


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')