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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 computationSun, 20 Dec 2009 06:09:28 -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/2009/Dec/20/t1261314783leax4xurhg4te6y.htm/, Retrieved Sat, 27 Apr 2024 08:29:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69870, Retrieved Sat, 27 Apr 2024 08:29:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

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] [SMP] [2009-12-20 13:09:28] [e458b4e05bf28a297f8af8d9f96e59d6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
210
220
212
191
180
195
136
196
182
166
147
125
164
170
171
140
155
156
141
167
171
206
187
124
163
154
226
125
162
145
98
128
159
209
150
125
214
193
140
205
192
192
186
150
246
282
264
336
301
376
416
344
326
351
249
258
311
343
278

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=69870&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=69870&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69870&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
118030.712745355515395
2162.66666666666721.877067001910082
3153.66666666666735.6353586747599128
4216.66666666666756.2402853564035196

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 180 & 30.7127453555153 & 95 \tabularnewline
2 & 162.666666666667 & 21.8770670019100 & 82 \tabularnewline
3 & 153.666666666667 & 35.6353586747599 & 128 \tabularnewline
4 & 216.666666666667 & 56.2402853564035 & 196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69870&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]180[/C][C]30.7127453555153[/C][C]95[/C][/ROW]
[ROW][C]2[/C][C]162.666666666667[/C][C]21.8770670019100[/C][C]82[/C][/ROW]
[ROW][C]3[/C][C]153.666666666667[/C][C]35.6353586747599[/C][C]128[/C][/ROW]
[ROW][C]4[/C][C]216.666666666667[/C][C]56.2402853564035[/C][C]196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69870&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69870&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
118030.712745355515395
2162.66666666666721.877067001910082
3153.66666666666735.6353586747599128
4216.66666666666756.2402853564035196






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-40.312142902935
beta0.428771427770447
S.D.0.21222022683024
T-STAT2.02040792329108
p-value0.180754367033287

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -40.312142902935 \tabularnewline
beta & 0.428771427770447 \tabularnewline
S.D. & 0.21222022683024 \tabularnewline
T-STAT & 2.02040792329108 \tabularnewline
p-value & 0.180754367033287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69870&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-40.312142902935[/C][/ROW]
[ROW][C]beta[/C][C]0.428771427770447[/C][/ROW]
[ROW][C]S.D.[/C][C]0.21222022683024[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.02040792329108[/C][/ROW]
[ROW][C]p-value[/C][C]0.180754367033287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69870&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69870&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-40.312142902935
beta0.428771427770447
S.D.0.21222022683024
T-STAT2.02040792329108
p-value0.180754367033287






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.37456883677895
beta1.91379531095051
S.D.1.24059964990632
T-STAT1.54263731341132
p-value0.262876649811793
Lambda-0.913795310950509

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.37456883677895 \tabularnewline
beta & 1.91379531095051 \tabularnewline
S.D. & 1.24059964990632 \tabularnewline
T-STAT & 1.54263731341132 \tabularnewline
p-value & 0.262876649811793 \tabularnewline
Lambda & -0.913795310950509 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69870&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.37456883677895[/C][/ROW]
[ROW][C]beta[/C][C]1.91379531095051[/C][/ROW]
[ROW][C]S.D.[/C][C]1.24059964990632[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.54263731341132[/C][/ROW]
[ROW][C]p-value[/C][C]0.262876649811793[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.913795310950509[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69870&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69870&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-6.37456883677895
beta1.91379531095051
S.D.1.24059964990632
T-STAT1.54263731341132
p-value0.262876649811793
Lambda-0.913795310950509


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')