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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 08 Dec 2008 09:04:45 -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/2008/Dec/08/t1228752394oic6pjrmo9ah7c6.htm/, Retrieved Thu, 16 May 2024 08:50:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30554, Retrieved Thu, 16 May 2024 08:50:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD    [Standard Deviation-Mean Plot] [Workshop 8] [2008-12-08 16:04:45] [d300b7a0882cee7d84584ad37a3d4ede] [Current]
Feedback Forum
2008-12-13 09:53:37 [Julie Govaerts] [reply] 
de p waarde is inderdaad groot en dit duidt er dus op dat bèta niet significant verschillend is van nul, dit betekent dat we niet naar de tweede tabel moeten kijken en lambda dus beter op 1 laten staan
2008-12-13 10:52:30 [Sofie Sergoynne] [reply] 
Hier is de p-waarde zeer groot en beta dus niet significant. We laten Lambda op 1 staan, zo wordt er niet getransformeerd.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,68
103,64
103,37
104,3
104,15
104,09
104,21
104,27
104
103,36
104,2
104,12
103,79
104,65
103,84
103,98
103,83
104,34
103,76
103,57
103,06
103,06
102,6
103,41
103,15
103,33
103,96
104,91
104,23
103,68
104,16
104,49
104,23
104,21
103,74
103,96
104,02
104,15
103,74
103,23
103,69
103,46
102,14
102,39
102,19
102,02
102,64
103,52
103,32
103,65
104,25
101,74
102,08
101,35
102,79
102,21
101,78
101,25
101,8
103
104,17
104,08
105,24
104,72
104,77
104,39
104,14
105,15
105,07
104,54
106,03
107,24
108,2
109,15
110,1
109,48
109,96
110,13
110,53
110,82
110,06
110,05
109,49
109,95

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30554&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30554&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1103.9491666666670.3437086063231540.939999999999998
2103.65750.567868822880782.05000000000001
3104.0041666666670.4850577909961441.75999999999999
4103.0991666666670.7781850484923042.13000000000001
5102.4350.9569031488942023
6104.9616666666670.9113310279060183.16000000000000
7109.8266666666670.6824332579198852.61999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.949166666667 & 0.343708606323154 & 0.939999999999998 \tabularnewline
2 & 103.6575 & 0.56786882288078 & 2.05000000000001 \tabularnewline
3 & 104.004166666667 & 0.485057790996144 & 1.75999999999999 \tabularnewline
4 & 103.099166666667 & 0.778185048492304 & 2.13000000000001 \tabularnewline
5 & 102.435 & 0.956903148894202 & 3 \tabularnewline
6 & 104.961666666667 & 0.911331027906018 & 3.16000000000000 \tabularnewline
7 & 109.826666666667 & 0.682433257919885 & 2.61999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30554&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]103.949166666667[/C][C]0.343708606323154[/C][C]0.939999999999998[/C][/ROW]
[ROW][C]2[/C][C]103.6575[/C][C]0.56786882288078[/C][C]2.05000000000001[/C][/ROW]
[ROW][C]3[/C][C]104.004166666667[/C][C]0.485057790996144[/C][C]1.75999999999999[/C][/ROW]
[ROW][C]4[/C][C]103.099166666667[/C][C]0.778185048492304[/C][C]2.13000000000001[/C][/ROW]
[ROW][C]5[/C][C]102.435[/C][C]0.956903148894202[/C][C]3[/C][/ROW]
[ROW][C]6[/C][C]104.961666666667[/C][C]0.911331027906018[/C][C]3.16000000000000[/C][/ROW]
[ROW][C]7[/C][C]109.826666666667[/C][C]0.682433257919885[/C][C]2.61999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30554&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30554&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
1103.9491666666670.3437086063231540.939999999999998
2103.65750.567868822880782.05000000000001
3104.0041666666670.4850577909961441.75999999999999
4103.0991666666670.7781850484923042.13000000000001
5102.4350.9569031488942023
6104.9616666666670.9113310279060183.16000000000000
7109.8266666666670.6824332579198852.61999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.28738175338666
beta-0.00585597673325549
S.D.0.0409415101994614
T-STAT-0.143032748541174
p-value0.891849777060799

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.28738175338666 \tabularnewline
beta & -0.00585597673325549 \tabularnewline
S.D. & 0.0409415101994614 \tabularnewline
T-STAT & -0.143032748541174 \tabularnewline
p-value & 0.891849777060799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30554&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.28738175338666[/C][/ROW]
[ROW][C]beta[/C][C]-0.00585597673325549[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0409415101994614[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.143032748541174[/C][/ROW]
[ROW][C]p-value[/C][C]0.891849777060799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30554&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30554&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)
alpha1.28738175338666
beta-0.00585597673325549
S.D.0.0409415101994614
T-STAT-0.143032748541174
p-value0.891849777060799






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.0547596743570743
beta-0.107857295067228
S.D.7.11501095511059
T-STAT-0.0151591186222638
p-value0.988491523240498
Lambda1.10785729506723

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.0547596743570743 \tabularnewline
beta & -0.107857295067228 \tabularnewline
S.D. & 7.11501095511059 \tabularnewline
T-STAT & -0.0151591186222638 \tabularnewline
p-value & 0.988491523240498 \tabularnewline
Lambda & 1.10785729506723 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30554&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0547596743570743[/C][/ROW]
[ROW][C]beta[/C][C]-0.107857295067228[/C][/ROW]
[ROW][C]S.D.[/C][C]7.11501095511059[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0151591186222638[/C][/ROW]
[ROW][C]p-value[/C][C]0.988491523240498[/C][/ROW]
[ROW][C]Lambda[/C][C]1.10785729506723[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30554&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30554&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)
alpha0.0547596743570743
beta-0.107857295067228
S.D.7.11501095511059
T-STAT-0.0151591186222638
p-value0.988491523240498
Lambda1.10785729506723


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')