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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, 05 Dec 2010 13:19:59 +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/05/t1291555146tc5vzvw4lp4qnp3.htm/, Retrieved Wed, 01 May 2024 13:47:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105382, Retrieved Wed, 01 May 2024 13:47:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W82
Estimated Impact99

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 deel 2 o...] [2010-12-05 13:19:59] [9a37dffdb284317d3f5f461f9b8f0111] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41086	
39690	
43129	
37863	
35953	
29133	
24693	
22205	
21725	
27192	
21790	
13253	
37702	
30364	
32609	
30212	
29965	
28352	
25814	
22414	
20506	
28806	
22228	
13971	
36845	
35338	
35022	
34777	
26887	
23970	
22780	
17351	
21382	
24561	
17409	
11514	
31514	
27071	
29462	
26105	
22397	
23843	
21705	
18089	
20764	
25316	
17704	
15548	
28029	
29383	
36438	
32034	
22679	
24319	
18004	
17537	
20366	
22782	
19169	
13807	
29743	
25591	
29096	
26482	
22405	
27044	
17970	
18730	
19684	
19785	
18479	
10698

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105382&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105382&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105382&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
129809.33333333339534.1464349161529876
226911.91666666676314.1373766022923731
3256538306.2242051039425331
423293.16666666674863.9772508688515966
523712.256639.8206865848422631
622142.255608.3585043786519045

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 29809.3333333333 & 9534.14643491615 & 29876 \tabularnewline
2 & 26911.9166666667 & 6314.13737660229 & 23731 \tabularnewline
3 & 25653 & 8306.22420510394 & 25331 \tabularnewline
4 & 23293.1666666667 & 4863.97725086885 & 15966 \tabularnewline
5 & 23712.25 & 6639.82068658484 & 22631 \tabularnewline
6 & 22142.25 & 5608.35850437865 & 19045 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105382&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]29809.3333333333[/C][C]9534.14643491615[/C][C]29876[/C][/ROW]
[ROW][C]2[/C][C]26911.9166666667[/C][C]6314.13737660229[/C][C]23731[/C][/ROW]
[ROW][C]3[/C][C]25653[/C][C]8306.22420510394[/C][C]25331[/C][/ROW]
[ROW][C]4[/C][C]23293.1666666667[/C][C]4863.97725086885[/C][C]15966[/C][/ROW]
[ROW][C]5[/C][C]23712.25[/C][C]6639.82068658484[/C][C]22631[/C][/ROW]
[ROW][C]6[/C][C]22142.25[/C][C]5608.35850437865[/C][C]19045[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105382&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105382&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
129809.33333333339534.1464349161529876
226911.91666666676314.1373766022923731
3256538306.2242051039425331
423293.16666666674863.9772508688515966
523712.256639.8206865848422631
622142.255608.3585043786519045






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5889.437038766
beta0.505559118946274
S.D.0.178206060929851
T-STAT2.83693560313464
p-value0.0470133361198828

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5889.437038766 \tabularnewline
beta & 0.505559118946274 \tabularnewline
S.D. & 0.178206060929851 \tabularnewline
T-STAT & 2.83693560313464 \tabularnewline
p-value & 0.0470133361198828 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105382&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5889.437038766[/C][/ROW]
[ROW][C]beta[/C][C]0.505559118946274[/C][/ROW]
[ROW][C]S.D.[/C][C]0.178206060929851[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.83693560313464[/C][/ROW]
[ROW][C]p-value[/C][C]0.0470133361198828[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105382&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105382&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-5889.437038766
beta0.505559118946274
S.D.0.178206060929851
T-STAT2.83693560313464
p-value0.0470133361198828






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.59236860367948
beta1.81632201037388
S.D.0.687487051387057
T-STAT2.6419726840081
p-value0.0574617220432712
Lambda-0.816322010373879

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.59236860367948 \tabularnewline
beta & 1.81632201037388 \tabularnewline
S.D. & 0.687487051387057 \tabularnewline
T-STAT & 2.6419726840081 \tabularnewline
p-value & 0.0574617220432712 \tabularnewline
Lambda & -0.816322010373879 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105382&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.59236860367948[/C][/ROW]
[ROW][C]beta[/C][C]1.81632201037388[/C][/ROW]
[ROW][C]S.D.[/C][C]0.687487051387057[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.6419726840081[/C][/ROW]
[ROW][C]p-value[/C][C]0.0574617220432712[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.816322010373879[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105382&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105382&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-9.59236860367948
beta1.81632201037388
S.D.0.687487051387057
T-STAT2.6419726840081
p-value0.0574617220432712
Lambda-0.816322010373879


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')