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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, 17 Dec 2013 15:36:58 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/17/t1387312774w1ysc38ogsp5a6m.htm/, Retrieved Fri, 29 Mar 2024 08:30:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232421, Retrieved Fri, 29 Mar 2024 08:30:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180
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       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- R PD          [(Partial) Autocorrelation Function] [ACR 1] [2013-12-03 18:19:48] [0ba55e3ce082ee2313a5fbafd157b436]
- RMP             [Standard Deviation-Mean Plot] [Stationariteit in...] [2013-12-03 18:59:09] [0ba55e3ce082ee2313a5fbafd157b436]
- R  D                [Standard Deviation-Mean Plot] [werkzoekenden] [2013-12-17 20:36:58] [2e4b2f9d3944a9ae720fcdd8099335ae] [Current]
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Dataseries X:
136524
132111
125326
122716
116615
113719
110737
112093
143565
149946
149147
134339
122683
115614
116566
111272
104609
101802
94542
93051
124129
130374
123946
114971
105531
104919
104782
101281
94545
93248
84031
87486
115867
120327
117008
108811
104519
106758
109337
109078
108293
106534
99197
103493
130676
137448
134704
123725
118277
121225
120528
118240
112514
107304
100001
102082
130455
135574
132540
119920
112454
109415
109843
106365
102304
97968
92462
92286
120092
126656
124144
114045
108120
105698
111203
110030
104009
99772
96301
97680
121563
134210
133111
124527
117589
115699
117830
115874
111267
107985
102185
102101
128932
135782
136971
126292
119260




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232421&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232421&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232421&T=0

As an alternative you can also use a 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 time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1128903.16666666714176.56511695139209
2112796.58333333312059.225095399637323
310315311594.709561613936296
4114480.16666666713329.750190889438251
5118221.66666666711350.826732672435573
6109002.83333333311396.651660053834370
7112185.33333333313180.942567574537909
8118208.91666666711764.270780308734870

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 128903.166666667 & 14176.565116951 & 39209 \tabularnewline
2 & 112796.583333333 & 12059.2250953996 & 37323 \tabularnewline
3 & 103153 & 11594.7095616139 & 36296 \tabularnewline
4 & 114480.166666667 & 13329.7501908894 & 38251 \tabularnewline
5 & 118221.666666667 & 11350.8267326724 & 35573 \tabularnewline
6 & 109002.833333333 & 11396.6516600538 & 34370 \tabularnewline
7 & 112185.333333333 & 13180.9425675745 & 37909 \tabularnewline
8 & 118208.916666667 & 11764.2707803087 & 34870 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232421&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]128903.166666667[/C][C]14176.565116951[/C][C]39209[/C][/ROW]
[ROW][C]2[/C][C]112796.583333333[/C][C]12059.2250953996[/C][C]37323[/C][/ROW]
[ROW][C]3[/C][C]103153[/C][C]11594.7095616139[/C][C]36296[/C][/ROW]
[ROW][C]4[/C][C]114480.166666667[/C][C]13329.7501908894[/C][C]38251[/C][/ROW]
[ROW][C]5[/C][C]118221.666666667[/C][C]11350.8267326724[/C][C]35573[/C][/ROW]
[ROW][C]6[/C][C]109002.833333333[/C][C]11396.6516600538[/C][C]34370[/C][/ROW]
[ROW][C]7[/C][C]112185.333333333[/C][C]13180.9425675745[/C][C]37909[/C][/ROW]
[ROW][C]8[/C][C]118208.916666667[/C][C]11764.2707803087[/C][C]34870[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232421&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232421&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1128903.16666666714176.56511695139209
2112796.58333333312059.225095399637323
310315311594.709561613936296
4114480.16666666713329.750190889438251
5118221.66666666711350.826732672435573
6109002.83333333311396.651660053834370
7112185.33333333313180.942567574537909
8118208.91666666711764.270780308734870







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3016.01613651815
beta0.0814926405935442
S.D.0.0465139955262067
T-STAT1.75200258914825
p-value0.130329095816762

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3016.01613651815 \tabularnewline
beta & 0.0814926405935442 \tabularnewline
S.D. & 0.0465139955262067 \tabularnewline
T-STAT & 1.75200258914825 \tabularnewline
p-value & 0.130329095816762 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232421&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3016.01613651815[/C][/ROW]
[ROW][C]beta[/C][C]0.0814926405935442[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0465139955262067[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.75200258914825[/C][/ROW]
[ROW][C]p-value[/C][C]0.130329095816762[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232421&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232421&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3016.01613651815
beta0.0814926405935442
S.D.0.0465139955262067
T-STAT1.75200258914825
p-value0.130329095816762







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.0280859807156
beta0.720389378370642
S.D.0.434036699971046
T-STAT1.6597430088716
p-value0.148035434558846
Lambda0.279610621629358

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.0280859807156 \tabularnewline
beta & 0.720389378370642 \tabularnewline
S.D. & 0.434036699971046 \tabularnewline
T-STAT & 1.6597430088716 \tabularnewline
p-value & 0.148035434558846 \tabularnewline
Lambda & 0.279610621629358 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232421&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.0280859807156[/C][/ROW]
[ROW][C]beta[/C][C]0.720389378370642[/C][/ROW]
[ROW][C]S.D.[/C][C]0.434036699971046[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.6597430088716[/C][/ROW]
[ROW][C]p-value[/C][C]0.148035434558846[/C][/ROW]
[ROW][C]Lambda[/C][C]0.279610621629358[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232421&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232421&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.0280859807156
beta0.720389378370642
S.D.0.434036699971046
T-STAT1.6597430088716
p-value0.148035434558846
Lambda0.279610621629358



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')