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Description of Statistical Computation

Author's title

Prijsevolutie korte sigaretten (Opgave 8, stap 3 (spreidings- en gemiddelde...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 30 Nov 2010 14:35:17 +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/2010/Nov/30/t1291127672m5tcn4fxhhbeyex.htm/, Retrieved Mon, 29 Apr 2024 12:42:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103540, Retrieved Mon, 29 Apr 2024 12:42:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact117

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] [Prijsevolutie kor...] [2010-11-30 14:35:17] [384a4ac05535402cc728b569fb124a5f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4.23
4.38
4.43
4.44
4.44
4.44
4.44
4.44
4.45
4.45
4.45
4.45
4.45
4.45
4.45
4.45
4.46
4.46
4.46
4.48
4.58
4.67
4.68
4.68
4.69
4.69
4.69
4.69
4.69
4.69
4.69
4.73
4.78
4.79
4.79
4.8
4.8
4.81
5.16
5.26
5.29
5.29
5.29
5.3
5.3
5.3
5.3
5.3
5.3
5.3
5.3
5.35
5.44
5.47
5.47
5.48
5.48
5.48
5.48
5.48
5.48
5.48
5.5
5.55
5.57
5.58
5.58
5.58
5.59
5.59
5.59
5.55

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=103540&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=103540&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103540&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
14.420.0628128533459080.220000000000000
24.52250.09964710459689950.230000000000000
34.726666666666670.04830458915396460.109999999999999
45.20.1886796226411320.5
55.419166666666670.08061787906068020.180000000000001
65.553333333333330.04271115105265150.109999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.42 & 0.062812853345908 & 0.220000000000000 \tabularnewline
2 & 4.5225 & 0.0996471045968995 & 0.230000000000000 \tabularnewline
3 & 4.72666666666667 & 0.0483045891539646 & 0.109999999999999 \tabularnewline
4 & 5.2 & 0.188679622641132 & 0.5 \tabularnewline
5 & 5.41916666666667 & 0.0806178790606802 & 0.180000000000001 \tabularnewline
6 & 5.55333333333333 & 0.0427111510526515 & 0.109999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103540&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]4.42[/C][C]0.062812853345908[/C][C]0.220000000000000[/C][/ROW]
[ROW][C]2[/C][C]4.5225[/C][C]0.0996471045968995[/C][C]0.230000000000000[/C][/ROW]
[ROW][C]3[/C][C]4.72666666666667[/C][C]0.0483045891539646[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]4[/C][C]5.2[/C][C]0.188679622641132[/C][C]0.5[/C][/ROW]
[ROW][C]5[/C][C]5.41916666666667[/C][C]0.0806178790606802[/C][C]0.180000000000001[/C][/ROW]
[ROW][C]6[/C][C]5.55333333333333[/C][C]0.0427111510526515[/C][C]0.109999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103540&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103540&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
14.420.0628128533459080.220000000000000
24.52250.09964710459689950.230000000000000
34.726666666666670.04830458915396460.109999999999999
45.20.1886796226411320.5
55.419166666666670.08061787906068020.180000000000001
65.553333333333330.04271115105265150.109999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0366498983539929
beta0.0101493597227795
S.D.0.0559090415581905
T-STAT0.181533423573645
p-value0.864776654930351

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0366498983539929 \tabularnewline
beta & 0.0101493597227795 \tabularnewline
S.D. & 0.0559090415581905 \tabularnewline
T-STAT & 0.181533423573645 \tabularnewline
p-value & 0.864776654930351 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103540&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0366498983539929[/C][/ROW]
[ROW][C]beta[/C][C]0.0101493597227795[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0559090415581905[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.181533423573645[/C][/ROW]
[ROW][C]p-value[/C][C]0.864776654930351[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103540&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103540&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)
alpha0.0366498983539929
beta0.0101493597227795
S.D.0.0559090415581905
T-STAT0.181533423573645
p-value0.864776654930351






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.63814194395844
beta0.0401890616265405
S.D.2.8043243353544
T-STAT0.0143311032607295
p-value0.989252132424887
Lambda0.95981093837346

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.63814194395844 \tabularnewline
beta & 0.0401890616265405 \tabularnewline
S.D. & 2.8043243353544 \tabularnewline
T-STAT & 0.0143311032607295 \tabularnewline
p-value & 0.989252132424887 \tabularnewline
Lambda & 0.95981093837346 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103540&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.63814194395844[/C][/ROW]
[ROW][C]beta[/C][C]0.0401890616265405[/C][/ROW]
[ROW][C]S.D.[/C][C]2.8043243353544[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0143311032607295[/C][/ROW]
[ROW][C]p-value[/C][C]0.989252132424887[/C][/ROW]
[ROW][C]Lambda[/C][C]0.95981093837346[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103540&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103540&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-2.63814194395844
beta0.0401890616265405
S.D.2.8043243353544
T-STAT0.0143311032607295
p-value0.989252132424887
Lambda0.95981093837346


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')