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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 computationMon, 01 Jun 2009 04:55:26 -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/01/t12438537740x62e8vakceadu6.htm/, Retrieved Mon, 13 May 2024 11:19:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40888, Retrieved Mon, 13 May 2024 11:19:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

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] [opgave 8-oefening...] [2009-06-01 10:55:26] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
356445
291705
310900
332340
257166
334551
317365
270863
317904
423141
317684
411063
371161
299023
326964
327146
303447
351994
320317
257151
320274
476982
301723
363567
338831
265802
307691
334207
303127
318863
292123
245155
284794
391604
304982
369552
356021
247577
277885
294032
310845
311023
298462
234188
297478
371017
291128
316374
326001
222302
227424
255428
278250
280335
241894
255075
255115
319482
270694
300209
283531
218924
236466
267980
219994
256052
230444
200778
240960
277837
209776
232065

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=40888&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=40888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40888&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
1328427.2549573.8496059162165975
2334979.08333333354429.1370540354219831
3313060.91666666741319.1545906173146449
4300502.538585.7768414029136829
5269350.7533305.5909997242103699
6239567.2526677.998685075982753

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 328427.25 & 49573.8496059162 & 165975 \tabularnewline
2 & 334979.083333333 & 54429.1370540354 & 219831 \tabularnewline
3 & 313060.916666667 & 41319.1545906173 & 146449 \tabularnewline
4 & 300502.5 & 38585.7768414029 & 136829 \tabularnewline
5 & 269350.75 & 33305.5909997242 & 103699 \tabularnewline
6 & 239567.25 & 26677.9986850759 & 82753 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40888&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]328427.25[/C][C]49573.8496059162[/C][C]165975[/C][/ROW]
[ROW][C]2[/C][C]334979.083333333[/C][C]54429.1370540354[/C][C]219831[/C][/ROW]
[ROW][C]3[/C][C]313060.916666667[/C][C]41319.1545906173[/C][C]146449[/C][/ROW]
[ROW][C]4[/C][C]300502.5[/C][C]38585.7768414029[/C][C]136829[/C][/ROW]
[ROW][C]5[/C][C]269350.75[/C][C]33305.5909997242[/C][C]103699[/C][/ROW]
[ROW][C]6[/C][C]239567.25[/C][C]26677.9986850759[/C][C]82753[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40888&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
1328427.2549573.8496059162165975
2334979.08333333354429.1370540354219831
3313060.91666666741319.1545906173146449
4300502.538585.7768414029136829
5269350.7533305.5909997242103699
6239567.2526677.998685075982753






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-39161.6175187109
beta0.268136232464239
S.D.0.0371312300939288
T-STAT7.22131294293105
p-value0.00195033373162085

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -39161.6175187109 \tabularnewline
beta & 0.268136232464239 \tabularnewline
S.D. & 0.0371312300939288 \tabularnewline
T-STAT & 7.22131294293105 \tabularnewline
p-value & 0.00195033373162085 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40888&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-39161.6175187109[/C][/ROW]
[ROW][C]beta[/C][C]0.268136232464239[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0371312300939288[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.22131294293105[/C][/ROW]
[ROW][C]p-value[/C][C]0.00195033373162085[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40888&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40888&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-39161.6175187109
beta0.268136232464239
S.D.0.0371312300939288
T-STAT7.22131294293105
p-value0.00195033373162085






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-14.3560211786616
beta1.97993640530327
S.D.0.207080540320914
T-STAT9.56119006756959
p-value0.000668463245878365
Lambda-0.979936405303268

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -14.3560211786616 \tabularnewline
beta & 1.97993640530327 \tabularnewline
S.D. & 0.207080540320914 \tabularnewline
T-STAT & 9.56119006756959 \tabularnewline
p-value & 0.000668463245878365 \tabularnewline
Lambda & -0.979936405303268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40888&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-14.3560211786616[/C][/ROW]
[ROW][C]beta[/C][C]1.97993640530327[/C][/ROW]
[ROW][C]S.D.[/C][C]0.207080540320914[/C][/ROW]
[ROW][C]T-STAT[/C][C]9.56119006756959[/C][/ROW]
[ROW][C]p-value[/C][C]0.000668463245878365[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.979936405303268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40888&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40888&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-14.3560211786616
beta1.97993640530327
S.D.0.207080540320914
T-STAT9.56119006756959
p-value0.000668463245878365
Lambda-0.979936405303268


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')