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Description of Statistical Computation

Author's title

Paper G12 Vervaardiging elektrische en elektronische apparaten en instrumen...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 13 Dec 2007 11:00:45 -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/2007/Dec/13/t1197567981xsyq041sa0phtg5.htm/, Retrieved Sun, 05 May 2024 18:41:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3681, Retrieved Sun, 05 May 2024 18:41:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper G12 Vervaardiging elektrische en elektronische apparaten en instrumenten
Estimated Impact201

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] [Paper G12 Vervaar...] [2007-12-13 18:00:45] [ae3f0dfb5dab6ea17524363c550229d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104,8
105,6
118,3
89,9
90,2
107
64,5
92,6
95,8
94,3
91,2
86,3
77,6
82,5
97,7
83,3
84,2
92,8
77,4
72,5
88,8
93,4
92,6
90,7
81,6
84,1
88,1
85,3
82,9
84,8
71,2
68,9
94,3
97,6
85,6
91,9
75,8
79,8
99
88,5
86,7
97,9
94,3
72,9
91,8
93,2
86,5
98,9
77,2
79,4
90,4
81,4
85,8
103,6
73,6
75,7
99,2
88,7
94,6
98,7
84,2
87,7
103,3
88,2
93,4
106,3
73,1
78,6
101,6
101,4
98,5
99
89,5
83,5
97,4
87,8
90,4
97,1
79,4
85

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3681&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3681&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3681&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
195.041666666666713.387881788687842.5
286.1257.75032257393218.3
384.69166666666678.35708282436729.5
488.7758.842369591913717.6
587.358333333333310.116634216911720.7
692.941666666666710.556381812425021.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 95.0416666666667 & 13.3878817886878 & 42.5 \tabularnewline
2 & 86.125 & 7.750322573932 & 18.3 \tabularnewline
3 & 84.6916666666667 & 8.3570828243672 & 9.5 \tabularnewline
4 & 88.775 & 8.8423695919137 & 17.6 \tabularnewline
5 & 87.3583333333333 & 10.1166342169117 & 20.7 \tabularnewline
6 & 92.9416666666667 & 10.5563818124250 & 21.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3681&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]95.0416666666667[/C][C]13.3878817886878[/C][C]42.5[/C][/ROW]
[ROW][C]2[/C][C]86.125[/C][C]7.750322573932[/C][C]18.3[/C][/ROW]
[ROW][C]3[/C][C]84.6916666666667[/C][C]8.3570828243672[/C][C]9.5[/C][/ROW]
[ROW][C]4[/C][C]88.775[/C][C]8.8423695919137[/C][C]17.6[/C][/ROW]
[ROW][C]5[/C][C]87.3583333333333[/C][C]10.1166342169117[/C][C]20.7[/C][/ROW]
[ROW][C]6[/C][C]92.9416666666667[/C][C]10.5563818124250[/C][C]21.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3681&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3681&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
195.041666666666713.387881788687842.5
286.1257.75032257393218.3
384.69166666666678.35708282436729.5
488.7758.842369591913717.6
587.358333333333310.116634216911720.7
692.941666666666710.556381812425021.5






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-30.0338523921543
beta0.447184298033081
S.D.0.116818985811724
T-STAT3.82801044646804
p-value0.0186498403377042

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -30.0338523921543 \tabularnewline
beta & 0.447184298033081 \tabularnewline
S.D. & 0.116818985811724 \tabularnewline
T-STAT & 3.82801044646804 \tabularnewline
p-value & 0.0186498403377042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3681&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-30.0338523921543[/C][/ROW]
[ROW][C]beta[/C][C]0.447184298033081[/C][/ROW]
[ROW][C]S.D.[/C][C]0.116818985811724[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.82801044646804[/C][/ROW]
[ROW][C]p-value[/C][C]0.0186498403377042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3681&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3681&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)
alpha-30.0338523921543
beta0.447184298033081
S.D.0.116818985811724
T-STAT3.82801044646804
p-value0.0186498403377042






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-15.1268633688058
beta3.87481744383344
S.D.1.02651304604682
T-STAT3.77473765068611
p-value0.0195243447797439
Lambda-2.87481744383344

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -15.1268633688058 \tabularnewline
beta & 3.87481744383344 \tabularnewline
S.D. & 1.02651304604682 \tabularnewline
T-STAT & 3.77473765068611 \tabularnewline
p-value & 0.0195243447797439 \tabularnewline
Lambda & -2.87481744383344 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3681&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-15.1268633688058[/C][/ROW]
[ROW][C]beta[/C][C]3.87481744383344[/C][/ROW]
[ROW][C]S.D.[/C][C]1.02651304604682[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.77473765068611[/C][/ROW]
[ROW][C]p-value[/C][C]0.0195243447797439[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.87481744383344[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3681&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3681&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-15.1268633688058
beta3.87481744383344
S.D.1.02651304604682
T-STAT3.77473765068611
p-value0.0195243447797439
Lambda-2.87481744383344


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')