FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 22 Dec 2010 19:15:16 +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/22/t12930451964g7o3c3weojrzbm.htm/, Retrieved Mon, 06 May 2024 08:35:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114513, Retrieved Mon, 06 May 2024 08:35:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD  [Variance Reduction Matrix] [WS9 - Variance Re...] [2010-12-04 11:04:59] [8ef49741e164ec6343c90c7935194465]
-   P     [Variance Reduction Matrix] [WS 9 VRM] [2010-12-05 14:01:21] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD      [(Partial) Autocorrelation Function] [paper ACF] [2010-12-10 10:47:04] [8214fe6d084e5ad7598b249a26cc9f06]
-   P         [(Partial) Autocorrelation Function] [paper acf met D=1] [2010-12-10 11:19:24] [8214fe6d084e5ad7598b249a26cc9f06]
- RMP           [Spectral Analysis] [paper - cum perio...] [2010-12-10 11:22:34] [8214fe6d084e5ad7598b249a26cc9f06]
-   P             [Spectral Analysis] [paper - cum perio...] [2010-12-10 11:27:22] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD              [Spectral Analysis] [cum periodogram 2 ] [2010-12-20 20:28:39] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                [Spectral Analysis] [cum per 2 paper] [2010-12-22 13:46:56] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                  [Spectral Analysis] [cum per 1 middeng...] [2010-12-22 19:06:59] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                     [Spectral Analysis] [cum per 2 middeng...] [2010-12-22 19:08:52] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                      [Spectral Analysis] [cum per 1 hoogges...] [2010-12-22 19:10:38] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                         [Spectral Analysis] [cum per 2 hoogges...] [2010-12-22 19:12:39] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD                            [Standard Deviation-Mean Plot] [sdmp laaggeschoolden] [2010-12-22 19:15:16] [b47314d83d48c7bf812ec2bcd743b159] [Current]
-    D                              [Standard Deviation-Mean Plot] [sdmp middengescho...] [2010-12-22 19:17:33] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                [Standard Deviation-Mean Plot] [sdmp hooggeschoolden] [2010-12-22 19:20:25] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                [Standard Deviation-Mean Plot] [sdmp hooggeschoolden] [2010-12-22 19:20:25] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD                                [ARIMA Backward Selection] [arima backward se...] [2010-12-22 19:29:00] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                                  [ARIMA Backward Selection] [arima backward se...] [2010-12-22 19:34:28] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                    [ARIMA Backward Selection] [arima backward se...] [2010-12-22 22:09:56] [8214fe6d084e5ad7598b249a26cc9f06]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104708
101817
97898
95559
92822
90848
101141
105841
93647
90923
89130
90212
93196
91861
90593
89895
88819
87924
96906
101217
98709
98139
95529
98577
100772
100180
99200
96251
94514
93780
105192
107682
99687
99436
102049
102673
105813
105056
103916
103513
101893
102503
113149
116696
108500
107800
105941
108742
111680
111270
110698
108517
107127
107088
116321
125045
116779
122887
120162
123198
123610
122293
121289
119393
117494
116693
125062
127281
120195
119804
117113
119240
115823
116281
113816
114632
112987
111633
116721
114850
112797
105368
102524
101327
102612
98873
95993
93244
90403
88539
98106
96963
90781
89253
87794
89810
90864
89025
87621
87718
83433
84535
92223
91052
88456
88706
89137
94066
99258
100673
102269
100833
99314
101764
108242
108148
104761
103772
103737
111043
109906
109335
107247
105690
102755
102280
110590
109122
102803
101424
99138

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=114513&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=114513&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114513&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
196212.16666666675914.9409715541316711
294280.41666666674468.2724230925913293
31001184063.9241671521913902
4106960.1666666674390.1999298713514803
5115064.3333333336549.6434647354317957
6120788.9166666673270.9901880938210588
7111563.255399.6961215003115394
893530.91666666674835.3041543579814818
9889032992.3997970616410633
10103651.1666666673784.9511785811011785

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 96212.1666666667 & 5914.94097155413 & 16711 \tabularnewline
2 & 94280.4166666667 & 4468.27242309259 & 13293 \tabularnewline
3 & 100118 & 4063.92416715219 & 13902 \tabularnewline
4 & 106960.166666667 & 4390.19992987135 & 14803 \tabularnewline
5 & 115064.333333333 & 6549.64346473543 & 17957 \tabularnewline
6 & 120788.916666667 & 3270.99018809382 & 10588 \tabularnewline
7 & 111563.25 & 5399.69612150031 & 15394 \tabularnewline
8 & 93530.9166666667 & 4835.30415435798 & 14818 \tabularnewline
9 & 88903 & 2992.39979706164 & 10633 \tabularnewline
10 & 103651.166666667 & 3784.95117858110 & 11785 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114513&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]96212.1666666667[/C][C]5914.94097155413[/C][C]16711[/C][/ROW]
[ROW][C]2[/C][C]94280.4166666667[/C][C]4468.27242309259[/C][C]13293[/C][/ROW]
[ROW][C]3[/C][C]100118[/C][C]4063.92416715219[/C][C]13902[/C][/ROW]
[ROW][C]4[/C][C]106960.166666667[/C][C]4390.19992987135[/C][C]14803[/C][/ROW]
[ROW][C]5[/C][C]115064.333333333[/C][C]6549.64346473543[/C][C]17957[/C][/ROW]
[ROW][C]6[/C][C]120788.916666667[/C][C]3270.99018809382[/C][C]10588[/C][/ROW]
[ROW][C]7[/C][C]111563.25[/C][C]5399.69612150031[/C][C]15394[/C][/ROW]
[ROW][C]8[/C][C]93530.9166666667[/C][C]4835.30415435798[/C][C]14818[/C][/ROW]
[ROW][C]9[/C][C]88903[/C][C]2992.39979706164[/C][C]10633[/C][/ROW]
[ROW][C]10[/C][C]103651.166666667[/C][C]3784.95117858110[/C][C]11785[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114513&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114513&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
196212.16666666675914.9409715541316711
294280.41666666674468.2724230925913293
31001184063.9241671521913902
4106960.1666666674390.1999298713514803
5115064.3333333336549.6434647354317957
6120788.9166666673270.9901880938210588
7111563.255399.6961215003115394
893530.91666666674835.3041543579814818
9889032992.3997970616410633
10103651.1666666673784.9511785811011785






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2483.50631874335
beta0.0202073691000991
S.D.0.0379575542204051
T-STAT0.532367522490057
p-value0.608935293564052

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2483.50631874335 \tabularnewline
beta & 0.0202073691000991 \tabularnewline
S.D. & 0.0379575542204051 \tabularnewline
T-STAT & 0.532367522490057 \tabularnewline
p-value & 0.608935293564052 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114513&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2483.50631874335[/C][/ROW]
[ROW][C]beta[/C][C]0.0202073691000991[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0379575542204051[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.532367522490057[/C][/ROW]
[ROW][C]p-value[/C][C]0.608935293564052[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114513&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114513&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)
alpha2483.50631874335
beta0.0202073691000991
S.D.0.0379575542204051
T-STAT0.532367522490057
p-value0.608935293564052






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.14066771340324
beta0.455678112507698
S.D.0.870231076396865
T-STAT0.523628866937737
p-value0.61472828188258
Lambda0.544321887492302

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.14066771340324 \tabularnewline
beta & 0.455678112507698 \tabularnewline
S.D. & 0.870231076396865 \tabularnewline
T-STAT & 0.523628866937737 \tabularnewline
p-value & 0.61472828188258 \tabularnewline
Lambda & 0.544321887492302 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114513&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.14066771340324[/C][/ROW]
[ROW][C]beta[/C][C]0.455678112507698[/C][/ROW]
[ROW][C]S.D.[/C][C]0.870231076396865[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.523628866937737[/C][/ROW]
[ROW][C]p-value[/C][C]0.61472828188258[/C][/ROW]
[ROW][C]Lambda[/C][C]0.544321887492302[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114513&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114513&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)
alpha3.14066771340324
beta0.455678112507698
S.D.0.870231076396865
T-STAT0.523628866937737
p-value0.61472828188258
Lambda0.544321887492302


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')