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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 computationMon, 15 Dec 2008 13:13:09 -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/15/t1229372061zplbv2ur0z77wzh.htm/, Retrieved Thu, 16 May 2024 01:08:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33806, Retrieved Thu, 16 May 2024 01:08:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184

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] [bel20 univariate ...] [2008-12-10 17:19:38] [74be16979710d4c4e7c6647856088456]
- RMPD  [Standard Deviation-Mean Plot] [] [2008-12-11 16:24:11] [3f7753907fc5bc4271bb94b38c29ceca]
-   P       [Standard Deviation-Mean Plot] [] [2008-12-15 20:13:09] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14525.87
14295.79
13830.14
14153.22
15418.03
16666.97
16505.21
17135.96
18033.25
17671
17544.22
17677.9
18470.97
18409.96
18941.6
19685.53
19834.71
19598.93
17039.97
16969.28
16973.38
16329.89
16153.34
15311.7
14760.87
14452.93
13720.95
13266.27
12708.47
13411.84
13975.55
12974.89
12151.11
11576.21
9996.83
10438.9
10511.22
10496.2
10300.79
9981.65
11448.79
11384.49
11717.46
10965.88
10352.27
9751.2
9354.01
8792.5
8721.14
8692.94
8570.73
8538.47
8169.75
7905.84
8145.82
8895.71
9676.31
9884.59
10637.44
10717.13
10205.29
10295.98
10892.76
10631.92
11441.08
11950.95
11037.54
11527.72
11383.89
10989.34
11079.42
11028.93
10973
11068.05
11394.84
11545.71
11809.38
11395.64
11082.38
11402.75
11716.87
12204.98
12986.62
13392.79
14368.05
15650.83
16102.64
16187.64
16311.54
17232.97
16397.83
14990.31
15147.55
15786.78
15934.09
16519.44
16101.07
16775.08
17286.32
17741.23
17128.37
17460.53
17611.14
18001.37
17974.77
16460.95
16235.39
16903.36
15543.76
15532.18
13731.31
13547.84
12602.93
13357.7
13995.33
14084.6
13168.91
12989.35
12123.53
9117.03
8531.45

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33806&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33806&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33806&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
116121.46333333331580.412212662684203.11
217809.93833333331539.513676698724523.01
312786.2351501.120107565144764.04
410421.3716666667875.2908955711222924.96
59046.3225955.378223447992811.29
611038.735503.5845522307591745.66
711747.7508333333760.8658676373952419.79
815885.8058333333769.6369361465582864.92
917139.965653.2786335303431900.3
1013316.20583333331674.534194647786426.73

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 16121.4633333333 & 1580.41221266268 & 4203.11 \tabularnewline
2 & 17809.9383333333 & 1539.51367669872 & 4523.01 \tabularnewline
3 & 12786.235 & 1501.12010756514 & 4764.04 \tabularnewline
4 & 10421.3716666667 & 875.290895571122 & 2924.96 \tabularnewline
5 & 9046.3225 & 955.37822344799 & 2811.29 \tabularnewline
6 & 11038.735 & 503.584552230759 & 1745.66 \tabularnewline
7 & 11747.7508333333 & 760.865867637395 & 2419.79 \tabularnewline
8 & 15885.8058333333 & 769.636936146558 & 2864.92 \tabularnewline
9 & 17139.965 & 653.278633530343 & 1900.3 \tabularnewline
10 & 13316.2058333333 & 1674.53419464778 & 6426.73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33806&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]16121.4633333333[/C][C]1580.41221266268[/C][C]4203.11[/C][/ROW]
[ROW][C]2[/C][C]17809.9383333333[/C][C]1539.51367669872[/C][C]4523.01[/C][/ROW]
[ROW][C]3[/C][C]12786.235[/C][C]1501.12010756514[/C][C]4764.04[/C][/ROW]
[ROW][C]4[/C][C]10421.3716666667[/C][C]875.290895571122[/C][C]2924.96[/C][/ROW]
[ROW][C]5[/C][C]9046.3225[/C][C]955.37822344799[/C][C]2811.29[/C][/ROW]
[ROW][C]6[/C][C]11038.735[/C][C]503.584552230759[/C][C]1745.66[/C][/ROW]
[ROW][C]7[/C][C]11747.7508333333[/C][C]760.865867637395[/C][C]2419.79[/C][/ROW]
[ROW][C]8[/C][C]15885.8058333333[/C][C]769.636936146558[/C][C]2864.92[/C][/ROW]
[ROW][C]9[/C][C]17139.965[/C][C]653.278633530343[/C][C]1900.3[/C][/ROW]
[ROW][C]10[/C][C]13316.2058333333[/C][C]1674.53419464778[/C][C]6426.73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33806&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33806&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
116121.46333333331580.412212662684203.11
217809.93833333331539.513676698724523.01
312786.2351501.120107565144764.04
410421.3716666667875.2908955711222924.96
59046.3225955.378223447992811.29
611038.735503.5845522307591745.66
711747.7508333333760.8658676373952419.79
815885.8058333333769.6369361465582864.92
917139.965653.2786335303431900.3
1013316.20583333331674.534194647786426.73






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha472.436447218545
beta0.0450009616754496
S.D.0.048881155886646
T-STAT0.920619835173405
p-value0.384169718990466

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 472.436447218545 \tabularnewline
beta & 0.0450009616754496 \tabularnewline
S.D. & 0.048881155886646 \tabularnewline
T-STAT & 0.920619835173405 \tabularnewline
p-value & 0.384169718990466 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33806&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]472.436447218545[/C][/ROW]
[ROW][C]beta[/C][C]0.0450009616754496[/C][/ROW]
[ROW][C]S.D.[/C][C]0.048881155886646[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.920619835173405[/C][/ROW]
[ROW][C]p-value[/C][C]0.384169718990466[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33806&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33806&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)
alpha472.436447218545
beta0.0450009616754496
S.D.0.048881155886646
T-STAT0.920619835173405
p-value0.384169718990466






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.82080315659176
beta0.535916405888199
S.D.0.627513650143071
T-STAT0.854031471293113
p-value0.417925270182677
Lambda0.464083594111801

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.82080315659176 \tabularnewline
beta & 0.535916405888199 \tabularnewline
S.D. & 0.627513650143071 \tabularnewline
T-STAT & 0.854031471293113 \tabularnewline
p-value & 0.417925270182677 \tabularnewline
Lambda & 0.464083594111801 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33806&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.82080315659176[/C][/ROW]
[ROW][C]beta[/C][C]0.535916405888199[/C][/ROW]
[ROW][C]S.D.[/C][C]0.627513650143071[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.854031471293113[/C][/ROW]
[ROW][C]p-value[/C][C]0.417925270182677[/C][/ROW]
[ROW][C]Lambda[/C][C]0.464083594111801[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33806&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33806&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)
alpha1.82080315659176
beta0.535916405888199
S.D.0.627513650143071
T-STAT0.854031471293113
p-value0.417925270182677
Lambda0.464083594111801


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')