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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 computationTue, 09 Dec 2008 06:12:48 -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/2008/Dec/09/t1228828624c8i90779mwdi1dd.htm/, Retrieved Sun, 19 May 2024 10:42:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31366, Retrieved Sun, 19 May 2024 10:42:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Spectral Analysis] [airline data] [2008-12-02 12:35:12] [0e5eff269cdcaf8789c45b6ee36b0c3d]
F RMPD    [Cross Correlation Function] [airline data] [2008-12-02 13:18:05] [0e5eff269cdcaf8789c45b6ee36b0c3d]
- RMPD      [(Partial) Autocorrelation Function] [paper] [2008-12-02 14:51:55] [0e5eff269cdcaf8789c45b6ee36b0c3d]
- RMP           [Standard Deviation-Mean Plot] [SDMP] [2008-12-09 13:12:48] [09074fbe368d26382bb94e5bb318a104] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
35810356.5
35492936.3
38937434.1
40059102.8
37708710.2
41570965.7
36333563
34181220.1
42593543.9
43119727.6
38497690.9
45473273.4
38399780.4
38882302.6
44051120.6
41677559.9
40699203.5
44150027.6
38225518.7
35447405.7
43075518.3
42302792
39743541.7
44670641.2
37123384
37668266.4
46117528.8
42273156.4
39404153.2
45799994.5
38602505.2
39454830.1
47427901.4
46497980.9
45057149.4
50615569.2
43033396.2
46013056.5
54222266.3
46417306.4
51046271.8
51201279.6
43475288.7
44968981.1
53939345.4
54549319.7
54072107.3
58434230.1
51158751
50039368
57872617.4
51642978.8
54534465.9
56094697.8
48189983.1
47492381
52987449.1
55719803.5
53922860.5
54931231.9

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=31366&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=31366&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31366&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
139148210.3753490043.6970820311292053.3
240943784.352869523.654413999223235.5
343003534.95833334471692.2656268813492185.2
450114404.09166675128257.4286257515400833.9
552882215.66666673232697.3714627910380236.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 39148210.375 & 3490043.69708203 & 11292053.3 \tabularnewline
2 & 40943784.35 & 2869523.65441399 & 9223235.5 \tabularnewline
3 & 43003534.9583333 & 4471692.26562688 & 13492185.2 \tabularnewline
4 & 50114404.0916667 & 5128257.42862575 & 15400833.9 \tabularnewline
5 & 52882215.6666667 & 3232697.37146279 & 10380236.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31366&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]39148210.375[/C][C]3490043.69708203[/C][C]11292053.3[/C][/ROW]
[ROW][C]2[/C][C]40943784.35[/C][C]2869523.65441399[/C][C]9223235.5[/C][/ROW]
[ROW][C]3[/C][C]43003534.9583333[/C][C]4471692.26562688[/C][C]13492185.2[/C][/ROW]
[ROW][C]4[/C][C]50114404.0916667[/C][C]5128257.42862575[/C][C]15400833.9[/C][/ROW]
[ROW][C]5[/C][C]52882215.6666667[/C][C]3232697.37146279[/C][C]10380236.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31366&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31366&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
139148210.3753490043.6970820311292053.3
240943784.352869523.654413999223235.5
343003534.95833334471692.2656268813492185.2
450114404.09166675128257.4286257515400833.9
552882215.66666673232697.3714627910380236.4






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1770726.81182664
beta0.0457272859035985
S.D.0.0863576960741152
T-STAT0.529510257711759
p-value0.633133427561373

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1770726.81182664 \tabularnewline
beta & 0.0457272859035985 \tabularnewline
S.D. & 0.0863576960741152 \tabularnewline
T-STAT & 0.529510257711759 \tabularnewline
p-value & 0.633133427561373 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31366&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1770726.81182664[/C][/ROW]
[ROW][C]beta[/C][C]0.0457272859035985[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0863576960741152[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.529510257711759[/C][/ROW]
[ROW][C]p-value[/C][C]0.633133427561373[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31366&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31366&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)
alpha1770726.81182664
beta0.0457272859035985
S.D.0.0863576960741152
T-STAT0.529510257711759
p-value0.633133427561373






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha5.54142667943242
beta0.544607407215809
S.D.1.00871275754723
T-STAT0.539903360139978
p-value0.626765114860205
Lambda0.455392592784191

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.54142667943242 \tabularnewline
beta & 0.544607407215809 \tabularnewline
S.D. & 1.00871275754723 \tabularnewline
T-STAT & 0.539903360139978 \tabularnewline
p-value & 0.626765114860205 \tabularnewline
Lambda & 0.455392592784191 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31366&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.54142667943242[/C][/ROW]
[ROW][C]beta[/C][C]0.544607407215809[/C][/ROW]
[ROW][C]S.D.[/C][C]1.00871275754723[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.539903360139978[/C][/ROW]
[ROW][C]p-value[/C][C]0.626765114860205[/C][/ROW]
[ROW][C]Lambda[/C][C]0.455392592784191[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31366&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31366&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)
alpha5.54142667943242
beta0.544607407215809
S.D.1.00871275754723
T-STAT0.539903360139978
p-value0.626765114860205
Lambda0.455392592784191


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')