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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 computationSat, 24 Nov 2007 03:42:12 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/24/t11959004345t8gz7wf63eec8l.htm/, Retrieved Fri, 03 May 2024 04:02:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6257, Retrieved Fri, 03 May 2024 04:02:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsG19Q1c
Estimated Impact238

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2007-11-24 10:42:12] [6b5c00822e2ce0f7cf73539c28d95782] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,7
103,75
103,85
104,02
104,13
104,17
104,18
104,2
104,5
104,78
104,88
104,89
104,9
104,95
105,24
105,35
105,44
105,46
105,47
105,48
105,75
106,1
106,19
106,23
106,24
106,25
106,35
106,48
106,52
106,55
106,55
106,56
106,89
107,09
107,24
107,28
107,3
107,31
107,47
107,35
107,31
107,32
107,32
107,34
107,53
107,72
107,75
107,79
107,81
107,9
107,8
107,86
107,8
107,74
107,75
107,83
107,8
107,81
107,86
107,83

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6257&T=0

[TABLE]
[ROW][C]Summary of compuational 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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6257&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6257&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1104.2541666666670.4203128344315441.19000000000000
2105.5466666666670.4435873047886922.48000000000000
3106.6666666666670.3674069661667833.43000000000001
4107.4591666666670.1911428943502923.77000000000001
5107.8158333333330.04501683186892783.77000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 104.254166666667 & 0.420312834431544 & 1.19000000000000 \tabularnewline
2 & 105.546666666667 & 0.443587304788692 & 2.48000000000000 \tabularnewline
3 & 106.666666666667 & 0.367406966166783 & 3.43000000000001 \tabularnewline
4 & 107.459166666667 & 0.191142894350292 & 3.77000000000001 \tabularnewline
5 & 107.815833333333 & 0.0450168318689278 & 3.77000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6257&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]104.254166666667[/C][C]0.420312834431544[/C][C]1.19000000000000[/C][/ROW]
[ROW][C]2[/C][C]105.546666666667[/C][C]0.443587304788692[/C][C]2.48000000000000[/C][/ROW]
[ROW][C]3[/C][C]106.666666666667[/C][C]0.367406966166783[/C][C]3.43000000000001[/C][/ROW]
[ROW][C]4[/C][C]107.459166666667[/C][C]0.191142894350292[/C][C]3.77000000000001[/C][/ROW]
[ROW][C]5[/C][C]107.815833333333[/C][C]0.0450168318689278[/C][C]3.77000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6257&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6257&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
1104.2541666666670.4203128344315441.19000000000000
2105.5466666666670.4435873047886922.48000000000000
3106.6666666666670.3674069661667833.43000000000001
4107.4591666666670.1911428943502923.77000000000001
5107.8158333333330.04501683186892783.77000000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha10.7910692515508
beta-0.0987092049744896
S.D.0.0361034652387599
T-STAT-2.73406456476421
p-value0.0716951193758445

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 10.7910692515508 \tabularnewline
beta & -0.0987092049744896 \tabularnewline
S.D. & 0.0361034652387599 \tabularnewline
T-STAT & -2.73406456476421 \tabularnewline
p-value & 0.0716951193758445 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6257&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.7910692515508[/C][/ROW]
[ROW][C]beta[/C][C]-0.0987092049744896[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0361034652387599[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.73406456476421[/C][/ROW]
[ROW][C]p-value[/C][C]0.0716951193758445[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6257&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6257&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)
alpha10.7910692515508
beta-0.0987092049744896
S.D.0.0361034652387599
T-STAT-2.73406456476421
p-value0.0716951193758445






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha243.974771369767
beta-52.5992438426612
S.D.26.630462132222
T-STAT-1.97515325049571
p-value0.142728873961928
Lambda53.5992438426612

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 243.974771369767 \tabularnewline
beta & -52.5992438426612 \tabularnewline
S.D. & 26.630462132222 \tabularnewline
T-STAT & -1.97515325049571 \tabularnewline
p-value & 0.142728873961928 \tabularnewline
Lambda & 53.5992438426612 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6257&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]243.974771369767[/C][/ROW]
[ROW][C]beta[/C][C]-52.5992438426612[/C][/ROW]
[ROW][C]S.D.[/C][C]26.630462132222[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.97515325049571[/C][/ROW]
[ROW][C]p-value[/C][C]0.142728873961928[/C][/ROW]
[ROW][C]Lambda[/C][C]53.5992438426612[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6257&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6257&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)
alpha243.974771369767
beta-52.5992438426612
S.D.26.630462132222
T-STAT-1.97515325049571
p-value0.142728873961928
Lambda53.5992438426612


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')