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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 26 Nov 2009 11:59:52 -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/Nov/26/t1259262050mgbj2znhwk8vtjk.htm/, Retrieved Sun, 28 Apr 2024 22:58:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60288, Retrieved Sun, 28 Apr 2024 22:58:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordstijdreeks=aantal bouwvergunningen
Estimated Impact140

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
- R  D          [Standard Deviation-Mean Plot] [heteroscedasticiteit] [2009-11-26 18:59:52] [03368d751914a6c247d86aff8eac7cbf] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2465
1932
1993
2243
1758
1806
2063
1823
2137
2428
2139
2265
2615
2070
2794
2190
2434
2520
2063
2068
2537
1898
2139
2408
2725
2201
2311
2548
2276
2351
2280
2057
2479
2379
2295
2456
2546
2844
2260
2981
2678
3440
2842
2450
2669
2570
2540
2318
2930
2946
2799
2695
2498
2260
2160
2058
2533
2150
2172
2155
3016

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=60288&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=60288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60288&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
12087.66666666667235.62656638817707
22311.33333333333276.080796254658896
32363.16666666667173.057968918107668
42678.16666666667320.7130786043481180
52446.33333333333329.661902101183888

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2087.66666666667 & 235.62656638817 & 707 \tabularnewline
2 & 2311.33333333333 & 276.080796254658 & 896 \tabularnewline
3 & 2363.16666666667 & 173.057968918107 & 668 \tabularnewline
4 & 2678.16666666667 & 320.713078604348 & 1180 \tabularnewline
5 & 2446.33333333333 & 329.661902101183 & 888 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60288&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]2087.66666666667[/C][C]235.62656638817[/C][C]707[/C][/ROW]
[ROW][C]2[/C][C]2311.33333333333[/C][C]276.080796254658[/C][C]896[/C][/ROW]
[ROW][C]3[/C][C]2363.16666666667[/C][C]173.057968918107[/C][C]668[/C][/ROW]
[ROW][C]4[/C][C]2678.16666666667[/C][C]320.713078604348[/C][C]1180[/C][/ROW]
[ROW][C]5[/C][C]2446.33333333333[/C][C]329.661902101183[/C][C]888[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60288&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
12087.66666666667235.62656638817707
22311.33333333333276.080796254658896
32363.16666666667173.057968918107668
42678.16666666667320.7130786043481180
52446.33333333333329.661902101183888






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-125.064421894315
beta0.164929536321203
S.D.0.145732330443254
T-STAT1.13172921766612
p-value0.340034492714250

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -125.064421894315 \tabularnewline
beta & 0.164929536321203 \tabularnewline
S.D. & 0.145732330443254 \tabularnewline
T-STAT & 1.13172921766612 \tabularnewline
p-value & 0.340034492714250 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60288&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-125.064421894315[/C][/ROW]
[ROW][C]beta[/C][C]0.164929536321203[/C][/ROW]
[ROW][C]S.D.[/C][C]0.145732330443254[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.13172921766612[/C][/ROW]
[ROW][C]p-value[/C][C]0.340034492714250[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60288&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60288&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-125.064421894315
beta0.164929536321203
S.D.0.145732330443254
T-STAT1.13172921766612
p-value0.340034492714250






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.22094008346956
beta1.38755701979308
S.D.1.48607521920733
T-STAT0.933705778724445
p-value0.419332815605160
Lambda-0.387557019793081

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.22094008346956 \tabularnewline
beta & 1.38755701979308 \tabularnewline
S.D. & 1.48607521920733 \tabularnewline
T-STAT & 0.933705778724445 \tabularnewline
p-value & 0.419332815605160 \tabularnewline
Lambda & -0.387557019793081 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60288&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.22094008346956[/C][/ROW]
[ROW][C]beta[/C][C]1.38755701979308[/C][/ROW]
[ROW][C]S.D.[/C][C]1.48607521920733[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.933705778724445[/C][/ROW]
[ROW][C]p-value[/C][C]0.419332815605160[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.387557019793081[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60288&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60288&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-5.22094008346956
beta1.38755701979308
S.D.1.48607521920733
T-STAT0.933705778724445
p-value0.419332815605160
Lambda-0.387557019793081


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')