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Description of Statistical Computation

Author's title

spreidings-en gemiddelde grafieken prijzen energiegrondstoffen - Charlotte ...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 03 Jun 2009 05:57:46 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jun/03/t12440303452csvdftocfu4gaq.htm/, Retrieved Sun, 12 May 2024 04:48:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41464, Retrieved Sun, 12 May 2024 04:48:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

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] [spreidings-en gem...] [2009-06-03 11:57:46] [16e291b2db388e9b7dc52bb84b5ee0ff] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106,8
114,3
105,7
90,1
91,6
97,7
100,8
104,6
95,9
102,7
104
107,9
113,8
113,8
123,1
125,1
137,6
134
140,3
152,1
150,6
167,3
153,2
142
154,4
158,5
180,9
181,3
172,4
192
199,3
215,4
214,3
201,5
190,5
196
215,7
209,4
214,1
237,8
239
237,8
251,5
248,8
215,4
201,2
203,1
214,2
188,9
203
213,3
228,5
228,2
240,9
258,8
248,5
269,2
289,6
323,4
317,2
322,8
340,9
368,2
388,5
441,2
474,3
483,9
417,9
365,9
263
199,4
157,2

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41464&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41464&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41464&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1101.8416666666677.0109600345502324.2
2137.74166666666716.633616472965153.5
3188.04166666666719.485400517652561
422417.796526729571850.3
5250.79166666666742.8758982589887134.5
6351.933333333333102.944312689684326.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 101.841666666667 & 7.01096003455023 & 24.2 \tabularnewline
2 & 137.741666666667 & 16.6336164729651 & 53.5 \tabularnewline
3 & 188.041666666667 & 19.4854005176525 & 61 \tabularnewline
4 & 224 & 17.7965267295718 & 50.3 \tabularnewline
5 & 250.791666666667 & 42.8758982589887 & 134.5 \tabularnewline
6 & 351.933333333333 & 102.944312689684 & 326.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41464&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]101.841666666667[/C][C]7.01096003455023[/C][C]24.2[/C][/ROW]
[ROW][C]2[/C][C]137.741666666667[/C][C]16.6336164729651[/C][C]53.5[/C][/ROW]
[ROW][C]3[/C][C]188.041666666667[/C][C]19.4854005176525[/C][C]61[/C][/ROW]
[ROW][C]4[/C][C]224[/C][C]17.7965267295718[/C][C]50.3[/C][/ROW]
[ROW][C]5[/C][C]250.791666666667[/C][C]42.8758982589887[/C][C]134.5[/C][/ROW]
[ROW][C]6[/C][C]351.933333333333[/C][C]102.944312689684[/C][C]326.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41464&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41464&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
1101.8416666666677.0109600345502324.2
2137.74166666666716.633616472965153.5
3188.04166666666719.485400517652561
422417.796526729571850.3
5250.79166666666742.8758982589887134.5
6351.933333333333102.944312689684326.7






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-42.0313893780608
beta0.365874796485652
S.D.0.0819957158167038
T-STAT4.46212089060289
p-value0.0111420720901072

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -42.0313893780608 \tabularnewline
beta & 0.365874796485652 \tabularnewline
S.D. & 0.0819957158167038 \tabularnewline
T-STAT & 4.46212089060289 \tabularnewline
p-value & 0.0111420720901072 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41464&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-42.0313893780608[/C][/ROW]
[ROW][C]beta[/C][C]0.365874796485652[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0819957158167038[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.46212089060289[/C][/ROW]
[ROW][C]p-value[/C][C]0.0111420720901072[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41464&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41464&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-42.0313893780608
beta0.365874796485652
S.D.0.0819957158167038
T-STAT4.46212089060289
p-value0.0111420720901072






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-7.08343104536227
beta1.94713681136543
S.D.0.37283461835124
T-STAT5.2225215029015
p-value0.00641639463812036
Lambda-0.947136811365426

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.08343104536227 \tabularnewline
beta & 1.94713681136543 \tabularnewline
S.D. & 0.37283461835124 \tabularnewline
T-STAT & 5.2225215029015 \tabularnewline
p-value & 0.00641639463812036 \tabularnewline
Lambda & -0.947136811365426 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41464&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.08343104536227[/C][/ROW]
[ROW][C]beta[/C][C]1.94713681136543[/C][/ROW]
[ROW][C]S.D.[/C][C]0.37283461835124[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.2225215029015[/C][/ROW]
[ROW][C]p-value[/C][C]0.00641639463812036[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.947136811365426[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41464&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41464&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-7.08343104536227
beta1.94713681136543
S.D.0.37283461835124
T-STAT5.2225215029015
p-value0.00641639463812036
Lambda-0.947136811365426


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')