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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 20 Dec 2011 14:23:17 -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/20/t1324409240nxusybx14gygwqa.htm/, Retrieved Mon, 06 May 2024 05:02:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158184, Retrieved Mon, 06 May 2024 05:02:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
F R PD    [Standard Deviation-Mean Plot] [Box-Cox transform...] [2010-12-02 20:27:12] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- R PD      [Standard Deviation-Mean Plot] [] [2011-12-03 19:25:57] [06c08141d7d783218a8164fd2ea166f2]
- R PD          [Standard Deviation-Mean Plot] [] [2011-12-20 19:23:17] [ce4468323d272130d499477f5e05a6d2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
164
148
152
144
155
125
153
146
138
190
192
192
147
133
163
150
129
131
145
137
138
168
176
188
139
143
150
154
137
129
128
140
143
151
177
184
151
134
164
126
131
125
127
143
143
160
190
182
138
136
152
127
151
130
119
153

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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158184&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158184&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158184&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' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1158.2522.095351218175967
2150.41666666666719.185497995447859
3147.91666666666717.222914616254456
414821.987599811133265

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 158.25 & 22.0953512181759 & 67 \tabularnewline
2 & 150.416666666667 & 19.1854979954478 & 59 \tabularnewline
3 & 147.916666666667 & 17.2229146162544 & 56 \tabularnewline
4 & 148 & 21.9875998111332 & 65 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158184&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]158.25[/C][C]22.0953512181759[/C][C]67[/C][/ROW]
[ROW][C]2[/C][C]150.416666666667[/C][C]19.1854979954478[/C][C]59[/C][/ROW]
[ROW][C]3[/C][C]147.916666666667[/C][C]17.2229146162544[/C][C]56[/C][/ROW]
[ROW][C]4[/C][C]148[/C][C]21.9875998111332[/C][C]65[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158184&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158184&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
1158.2522.095351218175967
2150.41666666666719.185497995447859
3147.91666666666717.222914616254456
414821.987599811133265






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-18.4338823970109
beta0.255096170744129
S.D.0.290218875575375
T-STAT0.878978564844851
p-value0.472120963866244

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -18.4338823970109 \tabularnewline
beta & 0.255096170744129 \tabularnewline
S.D. & 0.290218875575375 \tabularnewline
T-STAT & 0.878978564844851 \tabularnewline
p-value & 0.472120963866244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158184&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-18.4338823970109[/C][/ROW]
[ROW][C]beta[/C][C]0.255096170744129[/C][/ROW]
[ROW][C]S.D.[/C][C]0.290218875575375[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.878978564844851[/C][/ROW]
[ROW][C]p-value[/C][C]0.472120963866244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158184&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158184&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-18.4338823970109
beta0.255096170744129
S.D.0.290218875575375
T-STAT0.878978564844851
p-value0.472120963866244






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.92674574209799
beta1.97759658537889
S.D.2.2606230893958
T-STAT0.874801551242865
p-value0.473934084083313
Lambda-0.977596585378886

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.92674574209799 \tabularnewline
beta & 1.97759658537889 \tabularnewline
S.D. & 2.2606230893958 \tabularnewline
T-STAT & 0.874801551242865 \tabularnewline
p-value & 0.473934084083313 \tabularnewline
Lambda & -0.977596585378886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158184&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.92674574209799[/C][/ROW]
[ROW][C]beta[/C][C]1.97759658537889[/C][/ROW]
[ROW][C]S.D.[/C][C]2.2606230893958[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.874801551242865[/C][/ROW]
[ROW][C]p-value[/C][C]0.473934084083313[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.977596585378886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158184&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158184&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-6.92674574209799
beta1.97759658537889
S.D.2.2606230893958
T-STAT0.874801551242865
p-value0.473934084083313
Lambda-0.977596585378886


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 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')