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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 computationSun, 26 Dec 2010 16:44:05 +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/Dec/26/t12933816964empc92jfsgbb9a.htm/, Retrieved Mon, 06 May 2024 15:34:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115722, Retrieved Mon, 06 May 2024 15:34:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96

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 statistiek ] [2010-12-26 16:44:05] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
493
514
522
490
484
506
501
462
465
454
464
427
460
473
465
422
415
413
420
363
376
380
384
346
389
407
393
346
348
353
364
305
307
312
312
286
324
336
327
302
299
311
315
264
278
278
287
279
324
354
354
360
363
385
412
370
389
395
417
404

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115722&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115722&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115722&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1481.83333333333327.914914011016195
2409.7541.3502226002583127
3343.539.5370942050857121
430023.01382983417572
5377.2527.775479702919193

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 481.833333333333 & 27.9149140110161 & 95 \tabularnewline
2 & 409.75 & 41.3502226002583 & 127 \tabularnewline
3 & 343.5 & 39.5370942050857 & 121 \tabularnewline
4 & 300 & 23.013829834175 & 72 \tabularnewline
5 & 377.25 & 27.7754797029191 & 93 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115722&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]481.833333333333[/C][C]27.9149140110161[/C][C]95[/C][/ROW]
[ROW][C]2[/C][C]409.75[/C][C]41.3502226002583[/C][C]127[/C][/ROW]
[ROW][C]3[/C][C]343.5[/C][C]39.5370942050857[/C][C]121[/C][/ROW]
[ROW][C]4[/C][C]300[/C][C]23.013829834175[/C][C]72[/C][/ROW]
[ROW][C]5[/C][C]377.25[/C][C]27.7754797029191[/C][C]93[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115722&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115722&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
1481.83333333333327.914914011016195
2409.7541.3502226002583127
3343.539.5370942050857121
430023.01382983417572
5377.2527.775479702919193






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha25.4932196873837
beta0.0167990806605557
S.D.0.0668345520836845
T-STAT0.251353231776302
p-value0.817774854405663

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 25.4932196873837 \tabularnewline
beta & 0.0167990806605557 \tabularnewline
S.D. & 0.0668345520836845 \tabularnewline
T-STAT & 0.251353231776302 \tabularnewline
p-value & 0.817774854405663 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115722&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]25.4932196873837[/C][/ROW]
[ROW][C]beta[/C][C]0.0167990806605557[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0668345520836845[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.251353231776302[/C][/ROW]
[ROW][C]p-value[/C][C]0.817774854405663[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115722&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115722&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)
alpha25.4932196873837
beta0.0167990806605557
S.D.0.0668345520836845
T-STAT0.251353231776302
p-value0.817774854405663






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.41634813217944
beta0.340657878982009
S.D.0.789041006825218
T-STAT0.431736596748854
p-value0.695080095633079
Lambda0.659342121017991

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.41634813217944 \tabularnewline
beta & 0.340657878982009 \tabularnewline
S.D. & 0.789041006825218 \tabularnewline
T-STAT & 0.431736596748854 \tabularnewline
p-value & 0.695080095633079 \tabularnewline
Lambda & 0.659342121017991 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115722&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.41634813217944[/C][/ROW]
[ROW][C]beta[/C][C]0.340657878982009[/C][/ROW]
[ROW][C]S.D.[/C][C]0.789041006825218[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.431736596748854[/C][/ROW]
[ROW][C]p-value[/C][C]0.695080095633079[/C][/ROW]
[ROW][C]Lambda[/C][C]0.659342121017991[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115722&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115722&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)
alpha1.41634813217944
beta0.340657878982009
S.D.0.789041006825218
T-STAT0.431736596748854
p-value0.695080095633079
Lambda0.659342121017991


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')