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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, 11 Jan 2009 03:46:29 -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/Jan/11/t12316708369n907jfhy6rdngw.htm/, Retrieved Sat, 04 May 2024 21:25:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36860, Retrieved Sat, 04 May 2024 21:25:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact269

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [Opdracht 7_oefeni...] [2008-12-15 09:21:34] [4047c66d272f0b18d63fe49a1610bba9]
-    D  [Bootstrap Plot - Central Tendency] [Opdracht 7_Oefeni...] [2008-12-27 09:53:16] [74be16979710d4c4e7c6647856088456]
- RMPD    [Standard Deviation Plot] [Opdracht 8_Oefeni...] [2008-12-27 10:59:07] [4047c66d272f0b18d63fe49a1610bba9]
- RM D        [Standard Deviation-Mean Plot] [Opdracht 8_Oefeni...] [2009-01-11 10:46:29] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.60773
0.58933
0.60039
0.61342
0.6348
0.634
0.62915
0.62168
0.61328
0.6089
0.60857
0.62672
0.62291
0.62393
0.61838
0.62012
0.61659
0.6116
0.61573
0.61407
0.62823
0.64405
0.6387
0.63633
0.63059
0.62994
0.63709
0.64217
0.65711
0.66977
0.68255
0.68902
0.71322
0.70224
0.70045
0.69919
0.69693
0.69763
0.69278
0.70196
0.69215
0.6769
0.67124
0.66532
0.67157
0.66428
0.66576
0.66942
0.6813
0.69144
0.69862
0.695
0.69867
0.68968
0.69233
0.68293
0.68399
0.66895
0.68756
0.68527
0.6776
0.68137
0.67933
0.67922
0.68598
0.68297
0.68935
0.69463
0.6833
0.68666
0.68782
0.67669
0.67511
0.67254
0.67397
0.67286
0.66341
0.668
0.68021
0.67934
0.68136
0.67562
0.6744
0.67766
0.68887
0.69614
0.70896
0.72064

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=36860&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=36860&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36860&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
10.6156641666666670.01394539184777100.04547
20.624220.01049212345264080.03245
30.6711116666666670.03070802614459240.0832799999999999
40.6804950.01453034849109710.0376800000000000
50.6879783333333330.008346237947649690.02972
60.6837433333333330.005342271109374790.0179400000000000
70.674540.005105633252505580.0179499999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.615664166666667 & 0.0139453918477710 & 0.04547 \tabularnewline
2 & 0.62422 & 0.0104921234526408 & 0.03245 \tabularnewline
3 & 0.671111666666667 & 0.0307080261445924 & 0.0832799999999999 \tabularnewline
4 & 0.680495 & 0.0145303484910971 & 0.0376800000000000 \tabularnewline
5 & 0.687978333333333 & 0.00834623794764969 & 0.02972 \tabularnewline
6 & 0.683743333333333 & 0.00534227110937479 & 0.0179400000000000 \tabularnewline
7 & 0.67454 & 0.00510563325250558 & 0.0179499999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36860&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]0.615664166666667[/C][C]0.0139453918477710[/C][C]0.04547[/C][/ROW]
[ROW][C]2[/C][C]0.62422[/C][C]0.0104921234526408[/C][C]0.03245[/C][/ROW]
[ROW][C]3[/C][C]0.671111666666667[/C][C]0.0307080261445924[/C][C]0.0832799999999999[/C][/ROW]
[ROW][C]4[/C][C]0.680495[/C][C]0.0145303484910971[/C][C]0.0376800000000000[/C][/ROW]
[ROW][C]5[/C][C]0.687978333333333[/C][C]0.00834623794764969[/C][C]0.02972[/C][/ROW]
[ROW][C]6[/C][C]0.683743333333333[/C][C]0.00534227110937479[/C][C]0.0179400000000000[/C][/ROW]
[ROW][C]7[/C][C]0.67454[/C][C]0.00510563325250558[/C][C]0.0179499999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36860&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36860&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
10.6156641666666670.01394539184777100.04547
20.624220.01049212345264080.03245
30.6711116666666670.03070802614459240.0832799999999999
40.6804950.01453034849109710.0376800000000000
50.6879783333333330.008346237947649690.02972
60.6837433333333330.005342271109374790.0179400000000000
70.674540.005105633252505580.0179499999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0306873325390718
beta-0.0272419227908068
S.D.0.131847313492200
T-STAT-0.206617200375633
p-value0.844459219969316

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0306873325390718 \tabularnewline
beta & -0.0272419227908068 \tabularnewline
S.D. & 0.131847313492200 \tabularnewline
T-STAT & -0.206617200375633 \tabularnewline
p-value & 0.844459219969316 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36860&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0306873325390718[/C][/ROW]
[ROW][C]beta[/C][C]-0.0272419227908068[/C][/ROW]
[ROW][C]S.D.[/C][C]0.131847313492200[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.206617200375633[/C][/ROW]
[ROW][C]p-value[/C][C]0.844459219969316[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36860&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36860&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)
alpha0.0306873325390718
beta-0.0272419227908068
S.D.0.131847313492200
T-STAT-0.206617200375633
p-value0.844459219969316






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.90130695006311
beta-3.27886124941671
S.D.5.96524185946902
T-STAT-0.549661074380741
p-value0.606200529259471
Lambda4.27886124941671

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.90130695006311 \tabularnewline
beta & -3.27886124941671 \tabularnewline
S.D. & 5.96524185946902 \tabularnewline
T-STAT & -0.549661074380741 \tabularnewline
p-value & 0.606200529259471 \tabularnewline
Lambda & 4.27886124941671 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36860&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.90130695006311[/C][/ROW]
[ROW][C]beta[/C][C]-3.27886124941671[/C][/ROW]
[ROW][C]S.D.[/C][C]5.96524185946902[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.549661074380741[/C][/ROW]
[ROW][C]p-value[/C][C]0.606200529259471[/C][/ROW]
[ROW][C]Lambda[/C][C]4.27886124941671[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36860&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36860&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-5.90130695006311
beta-3.27886124941671
S.D.5.96524185946902
T-STAT-0.549661074380741
p-value0.606200529259471
Lambda4.27886124941671


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')