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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 computationWed, 26 May 2010 17:49:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/26/t12748962053ucfwfz9n3nma3c.htm/, Retrieved Fri, 03 May 2024 07:46:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76530, Retrieved Fri, 03 May 2024 07:46:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact120

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] [] [2010-05-26 17:49:36] [ba71a47f11e8062985d77fe3913d8d26] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
225
243
270
289
273
274
220
271
288
276
266
239
201
242
239
273
280
294
212
264
272
262
238
227
250
245
270
288
298
281
218
284
281
277
276
222
255
267
261
263
264
278
248
320
305
301
274
220
235
252
272
280
305
299
246
307
325
302
274
251
272
253
292
288
258
295
231
250
268

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=76530&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=76530&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76530&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
1261.16666666666723.435921664027369
2250.33333333333328.429604714846593
3265.83333333333326.034359580905480
4271.33333333333327.1839970749281100
527928.790781352875690

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 261.166666666667 & 23.4359216640273 & 69 \tabularnewline
2 & 250.333333333333 & 28.4296047148465 & 93 \tabularnewline
3 & 265.833333333333 & 26.0343595809054 & 80 \tabularnewline
4 & 271.333333333333 & 27.1839970749281 & 100 \tabularnewline
5 & 279 & 28.7907813528756 & 90 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76530&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]261.166666666667[/C][C]23.4359216640273[/C][C]69[/C][/ROW]
[ROW][C]2[/C][C]250.333333333333[/C][C]28.4296047148465[/C][C]93[/C][/ROW]
[ROW][C]3[/C][C]265.833333333333[/C][C]26.0343595809054[/C][C]80[/C][/ROW]
[ROW][C]4[/C][C]271.333333333333[/C][C]27.1839970749281[/C][C]100[/C][/ROW]
[ROW][C]5[/C][C]279[/C][C]28.7907813528756[/C][C]90[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76530&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76530&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
1261.16666666666723.435921664027369
2250.33333333333328.429604714846593
3265.83333333333326.034359580905480
4271.33333333333327.1839970749281100
527928.790781352875690






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha16.0857069474077
beta0.0402556838944596
S.D.0.113292974788049
T-STAT0.355323743328048
p-value0.745861193077735

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 16.0857069474077 \tabularnewline
beta & 0.0402556838944596 \tabularnewline
S.D. & 0.113292974788049 \tabularnewline
T-STAT & 0.355323743328048 \tabularnewline
p-value & 0.745861193077735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76530&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]16.0857069474077[/C][/ROW]
[ROW][C]beta[/C][C]0.0402556838944596[/C][/ROW]
[ROW][C]S.D.[/C][C]0.113292974788049[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.355323743328048[/C][/ROW]
[ROW][C]p-value[/C][C]0.745861193077735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76530&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76530&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)
alpha16.0857069474077
beta0.0402556838944596
S.D.0.113292974788049
T-STAT0.355323743328048
p-value0.745861193077735






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.14725289125864
beta0.382991983033404
S.D.1.15375850446993
T-STAT0.3319516012663
p-value0.761765117514942
Lambda0.617008016966596

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.14725289125864 \tabularnewline
beta & 0.382991983033404 \tabularnewline
S.D. & 1.15375850446993 \tabularnewline
T-STAT & 0.3319516012663 \tabularnewline
p-value & 0.761765117514942 \tabularnewline
Lambda & 0.617008016966596 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76530&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.14725289125864[/C][/ROW]
[ROW][C]beta[/C][C]0.382991983033404[/C][/ROW]
[ROW][C]S.D.[/C][C]1.15375850446993[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.3319516012663[/C][/ROW]
[ROW][C]p-value[/C][C]0.761765117514942[/C][/ROW]
[ROW][C]Lambda[/C][C]0.617008016966596[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76530&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76530&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)
alpha1.14725289125864
beta0.382991983033404
S.D.1.15375850446993
T-STAT0.3319516012663
p-value0.761765117514942
Lambda0.617008016966596


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')