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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, 02 Dec 2008 06:33:36 -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/02/t1228224855k9f7r0u5u2v37gq.htm/, Retrieved Fri, 17 May 2024 04:18:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27759, Retrieved Fri, 17 May 2024 04:18:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact205

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Standard Deviation-Mean Plot] [] [2008-12-02 13:33:36] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-04 09:54:51 [72e979bcc364082694890d2eccc1a66f] [reply] 
De p-value ligt hier boven de 5%, wat niet meer binnen het betrouwbaarheidsinterval ligt. Hierdoor is de weergegeven lambda-waarde niet betrouwbaar. De student heeft dit goed opgemerkt.
2008-12-06 10:50:18 [Bert Moons] [reply] 
Er is correct geconcludeerd dat de lambda waarde niet betrouwbaar is (P-waarden van 0.67 en 0.12).
2008-12-06 16:29:23 [Bénédicte Soens] [reply] 
Dit is een goede uitleg bij dit onderdeel van de vraag
2008-12-09 14:05:30 [Jules De Bruycker] [reply] 
Het was een goed idee om zo de vraag duidelijk te kunnen beantwoorden.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4,56
4,41
4,33
4,20
4,25
4,25
4,19
4,17
4,21
4,21
4,17
4,16
4,19
4,08
4,06
3,98
3,82
3,82
3,72
3,56
3,57
3,49
3,32
3,23
3,04
3,00
2,82
2,73
2,59
2,58
2,53
2,31
2,31
2,30
2,07
2,07
2,06
2,06
2,05
2,05
2,05
2,05
2,05
2,06
2,07
2,08
2,05
2,03
2,02
2,02
2,01
2,01
2,01
2,01
2,01
2,01
2,03
2,04
2,03
2,05
2,08
2,06
2,09
2,19
2,56
2,54
2,63
2,78
2,84
3,02
3,28
3,29
3,29
3,29
3,32
3,34
3,32
3,30
3,30
3,30
3,31
3,35
3,48
3,76
4,06
4,51
4,52
4,53
4,63
4,79
4,77
4,77
4,77
4,81
4,83
4,76
4,61

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27759&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27759&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27759&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.259166666666670.1195794398056890.399999999999999
23.736666666666670.3091728946526180.96
32.529166666666670.3280925128217600.97
42.0550.01243163121016130.0500000000000003
52.020833333333330.01378954368902450.04
62.613333333333330.4471187219465891.23
73.363333333333330.1351990675958520.47
84.645833333333330.219936285539630.77

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.25916666666667 & 0.119579439805689 & 0.399999999999999 \tabularnewline
2 & 3.73666666666667 & 0.309172894652618 & 0.96 \tabularnewline
3 & 2.52916666666667 & 0.328092512821760 & 0.97 \tabularnewline
4 & 2.055 & 0.0124316312101613 & 0.0500000000000003 \tabularnewline
5 & 2.02083333333333 & 0.0137895436890245 & 0.04 \tabularnewline
6 & 2.61333333333333 & 0.447118721946589 & 1.23 \tabularnewline
7 & 3.36333333333333 & 0.135199067595852 & 0.47 \tabularnewline
8 & 4.64583333333333 & 0.21993628553963 & 0.77 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27759&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]4.25916666666667[/C][C]0.119579439805689[/C][C]0.399999999999999[/C][/ROW]
[ROW][C]2[/C][C]3.73666666666667[/C][C]0.309172894652618[/C][C]0.96[/C][/ROW]
[ROW][C]3[/C][C]2.52916666666667[/C][C]0.328092512821760[/C][C]0.97[/C][/ROW]
[ROW][C]4[/C][C]2.055[/C][C]0.0124316312101613[/C][C]0.0500000000000003[/C][/ROW]
[ROW][C]5[/C][C]2.02083333333333[/C][C]0.0137895436890245[/C][C]0.04[/C][/ROW]
[ROW][C]6[/C][C]2.61333333333333[/C][C]0.447118721946589[/C][C]1.23[/C][/ROW]
[ROW][C]7[/C][C]3.36333333333333[/C][C]0.135199067595852[/C][C]0.47[/C][/ROW]
[ROW][C]8[/C][C]4.64583333333333[/C][C]0.21993628553963[/C][C]0.77[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27759&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27759&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
14.259166666666670.1195794398056890.399999999999999
23.736666666666670.3091728946526180.96
32.529166666666670.3280925128217600.97
42.0550.01243163121016130.0500000000000003
52.020833333333330.01378954368902450.04
62.613333333333330.4471187219465891.23
73.363333333333330.1351990675958520.47
84.645833333333330.219936285539630.77






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.110667760828975
beta0.027751209619249
S.D.0.0626361367243162
T-STAT0.443054298533639
p-value0.673253695724777

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.110667760828975 \tabularnewline
beta & 0.027751209619249 \tabularnewline
S.D. & 0.0626361367243162 \tabularnewline
T-STAT & 0.443054298533639 \tabularnewline
p-value & 0.673253695724777 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27759&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.110667760828975[/C][/ROW]
[ROW][C]beta[/C][C]0.027751209619249[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0626361367243162[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.443054298533639[/C][/ROW]
[ROW][C]p-value[/C][C]0.673253695724777[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27759&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27759&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)
alpha0.110667760828975
beta0.027751209619249
S.D.0.0626361367243162
T-STAT0.443054298533639
p-value0.673253695724777






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.99579214777484
beta2.55565568008231
S.D.1.44842156780167
T-STAT1.76444188411329
p-value0.128105495777844
Lambda-1.55565568008231

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.99579214777484 \tabularnewline
beta & 2.55565568008231 \tabularnewline
S.D. & 1.44842156780167 \tabularnewline
T-STAT & 1.76444188411329 \tabularnewline
p-value & 0.128105495777844 \tabularnewline
Lambda & -1.55565568008231 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27759&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.99579214777484[/C][/ROW]
[ROW][C]beta[/C][C]2.55565568008231[/C][/ROW]
[ROW][C]S.D.[/C][C]1.44842156780167[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.76444188411329[/C][/ROW]
[ROW][C]p-value[/C][C]0.128105495777844[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.55565568008231[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27759&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27759&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-4.99579214777484
beta2.55565568008231
S.D.1.44842156780167
T-STAT1.76444188411329
p-value0.128105495777844
Lambda-1.55565568008231


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')