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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, 27 Dec 2011 10:40:57 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/27/t1325000477tvb3qk6k71l43pw.htm/, Retrieved Wed, 15 May 2024 18:20:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160858, Retrieved Wed, 15 May 2024 18:20:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact113

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] [Bestellingen Boeing] [2011-12-27 15:40:57] [e09593412f775de82555261d5bbd0b3f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
20
32
11
14
199
162
88
89
24
36
142
193
39
25
95
144
33
131
31
24
160
52
57
210
13
52
96
133
74
131
129
74
127
55
175
185
34
115
95
58
63
56
70
32
32
14
6
23
18
4
6
17
20
20
44
32
20
14
9
59
10
47
43
34
5
49
130
10
117
108
17
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'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160858&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160858&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160858&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
184.166666666666772.3172723406233188
283.416666666666763.1354364310039186
3103.66666666666751.8517700817056172
449.833333333333332.7298399666485109
521.916666666666716.008283840410655
652.083333333333343.5419512097416125

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 84.1666666666667 & 72.3172723406233 & 188 \tabularnewline
2 & 83.4166666666667 & 63.1354364310039 & 186 \tabularnewline
3 & 103.666666666667 & 51.8517700817056 & 172 \tabularnewline
4 & 49.8333333333333 & 32.7298399666485 & 109 \tabularnewline
5 & 21.9166666666667 & 16.0082838404106 & 55 \tabularnewline
6 & 52.0833333333333 & 43.5419512097416 & 125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160858&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]84.1666666666667[/C][C]72.3172723406233[/C][C]188[/C][/ROW]
[ROW][C]2[/C][C]83.4166666666667[/C][C]63.1354364310039[/C][C]186[/C][/ROW]
[ROW][C]3[/C][C]103.666666666667[/C][C]51.8517700817056[/C][C]172[/C][/ROW]
[ROW][C]4[/C][C]49.8333333333333[/C][C]32.7298399666485[/C][C]109[/C][/ROW]
[ROW][C]5[/C][C]21.9166666666667[/C][C]16.0082838404106[/C][C]55[/C][/ROW]
[ROW][C]6[/C][C]52.0833333333333[/C][C]43.5419512097416[/C][C]125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160858&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160858&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
184.166666666666772.3172723406233188
283.416666666666763.1354364310039186
3103.66666666666751.8517700817056172
449.833333333333332.7298399666485109
521.916666666666716.008283840410655
652.083333333333343.5419512097416125






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.59602042894057
beta0.577114780754668
S.D.0.18627976452899
T-STAT3.09810774248028
p-value0.0362876405361516

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.59602042894057 \tabularnewline
beta & 0.577114780754668 \tabularnewline
S.D. & 0.18627976452899 \tabularnewline
T-STAT & 3.09810774248028 \tabularnewline
p-value & 0.0362876405361516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160858&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.59602042894057[/C][/ROW]
[ROW][C]beta[/C][C]0.577114780754668[/C][/ROW]
[ROW][C]S.D.[/C][C]0.18627976452899[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.09810774248028[/C][/ROW]
[ROW][C]p-value[/C][C]0.0362876405361516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160858&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160858&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)
alpha8.59602042894057
beta0.577114780754668
S.D.0.18627976452899
T-STAT3.09810774248028
p-value0.0362876405361516






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.0267460683227416
beta0.910121343629843
S.D.0.170105533556148
T-STAT5.35033355237343
p-value0.00588432542498338
Lambda0.0898786563701568

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.0267460683227416 \tabularnewline
beta & 0.910121343629843 \tabularnewline
S.D. & 0.170105533556148 \tabularnewline
T-STAT & 5.35033355237343 \tabularnewline
p-value & 0.00588432542498338 \tabularnewline
Lambda & 0.0898786563701568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160858&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0267460683227416[/C][/ROW]
[ROW][C]beta[/C][C]0.910121343629843[/C][/ROW]
[ROW][C]S.D.[/C][C]0.170105533556148[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.35033355237343[/C][/ROW]
[ROW][C]p-value[/C][C]0.00588432542498338[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0898786563701568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160858&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160858&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)
alpha0.0267460683227416
beta0.910121343629843
S.D.0.170105533556148
T-STAT5.35033355237343
p-value0.00588432542498338
Lambda0.0898786563701568


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')