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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 computationFri, 12 Dec 2008 05:13:32 -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/12/t1229084203osppeqlcqjtxj7h.htm/, Retrieved Sun, 19 May 2024 08:00:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32606, Retrieved Sun, 19 May 2024 08:00:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact230

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2008-12-12 12:13:32] [fa8b44cd657c07c6ee11bb2476ca3f8d] [Current]
-   PD    [Standard Deviation-Mean Plot] [duurz cons] [2008-12-12 12:19:08] [fad8a251ac01c156a8ae23a83577546f]
-    D    [Standard Deviation-Mean Plot] [Niet-duurz cons] [2008-12-12 12:32:54] [fad8a251ac01c156a8ae23a83577546f]
-    D    [Standard Deviation-Mean Plot] [cons] [2008-12-12 12:36:48] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Box-Cox Normality Plot] [Consumptiegoederen] [2008-12-12 12:45:51] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Box-Cox Normality Plot] [niet-duurz cons] [2008-12-12 12:50:07] [fad8a251ac01c156a8ae23a83577546f]
- RMP     [Box-Cox Normality Plot] [Duurzame cons] [2008-12-12 12:53:42] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Box-Cox Normality Plot] [Investeringsgoederen] [2008-12-12 13:00:54] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Variance Reduction Matrix] [Investeringsgoederen] [2008-12-12 13:12:24] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Variance Reduction Matrix] [Investeringsgoederen] [2008-12-12 13:17:50] [fad8a251ac01c156a8ae23a83577546f]
- RMP     [Variance Reduction Matrix] [Duurz cons] [2008-12-12 13:21:04] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Variance Reduction Matrix] [niet-duurz cons] [2008-12-12 13:23:51] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [Variance Reduction Matrix] [Consumptiegoederen] [2008-12-12 13:27:46] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [(Partial) Autocorrelation Function] [Consumptiegoederen] [2008-12-12 13:34:26] [fad8a251ac01c156a8ae23a83577546f]
- RMPD    [(Partial) Autocorrelation Function] [Consumptiegoederen] [2008-12-12 13:39:25] [fad8a251ac01c156a8ae23a83577546f]
-   P       [(Partial) Autocorrelation Function] [auto corr cons] [2008-12-19 10:50:23] [fad8a251ac01c156a8ae23a83577546f]
-   P       [(Partial) Autocorrelation Function] [auto corr cons] [2008-12-19 10:53:37] [fad8a251ac01c156a8ae23a83577546f]
-   PD        [(Partial) Autocorrelation Function] [autocorr cons] [2008-12-21 18:00:56] [fad8a251ac01c156a8ae23a83577546f]
-   P         [(Partial) Autocorrelation Function] [autocorr cons D] [2008-12-21 18:04:22] [fad8a251ac01c156a8ae23a83577546f]
- RMPD          [ARIMA Backward Selection] [Arima backw sel n...] [2008-12-22 10:23:57] [fad8a251ac01c156a8ae23a83577546f]
-    D            [ARIMA Backward Selection] [arima backw sel cons] [2008-12-22 10:27:01] [fad8a251ac01c156a8ae23a83577546f]
-    D            [ARIMA Backward Selection] [arima backw sel d...] [2008-12-22 10:29:20] [fad8a251ac01c156a8ae23a83577546f]
- RMPD              [ARIMA Forecasting] [] [2008-12-22 19:10:36] [b98453cac15ba1066b407e146608df68]
-                     [ARIMA Forecasting] [forecasting duur ...] [2008-12-22 19:52:23] [fad8a251ac01c156a8ae23a83577546f]
-   PD            [ARIMA Backward Selection] [arima backw sel inv] [2008-12-22 10:34:37] [fad8a251ac01c156a8ae23a83577546f]
-   P               [ARIMA Backward Selection] [foutmelding arima...] [2008-12-22 10:39:41] [fad8a251ac01c156a8ae23a83577546f]
-   PD                [ARIMA Backward Selection] [arima backw sel inv] [2008-12-22 12:07:05] [fad8a251ac01c156a8ae23a83577546f]
- RMPD            [ARIMA Forecasting] [forecast inv] [2008-12-22 14:22:41] [fad8a251ac01c156a8ae23a83577546f]
- RMP             [ARIMA Forecasting] [forecast niet-duu...] [2008-12-22 14:29:00] [fad8a251ac01c156a8ae23a83577546f]
- RMPD            [ARIMA Forecasting] [forecast consumpt...] [2008-12-22 14:31:21] [fad8a251ac01c156a8ae23a83577546f]
- RMPD            [ARIMA Forecasting] [forecasting duur ...] [2008-12-22 16:42:36] [fad8a251ac01c156a8ae23a83577546f]
-   P       [(Partial) Autocorrelation Function] [auto corr cons] [2008-12-19 10:57:15] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr nd cons] [2008-12-19 11:02:29] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr nd cons] [2008-12-19 11:05:07] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr nd cons] [2008-12-19 11:09:15] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr nd cons] [2008-12-19 11:09:15] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr nd cons] [2008-12-19 11:09:15] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr d cons] [2008-12-19 11:13:02] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr d cons] [2008-12-19 11:14:51] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr d cons] [2008-12-19 11:16:22] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr inv] [2008-12-19 11:19:14] [fad8a251ac01c156a8ae23a83577546f]
-   P         [(Partial) Autocorrelation Function] [autocorr inv] [2008-12-21 16:50:49] [fad8a251ac01c156a8ae23a83577546f]
-   PD        [(Partial) Autocorrelation Function] [autocorr inv D] [2008-12-21 16:54:57] [fad8a251ac01c156a8ae23a83577546f]
-   PD        [(Partial) Autocorrelation Function] [autocorr duur cons] [2008-12-21 17:16:16] [fad8a251ac01c156a8ae23a83577546f]
-   PD        [(Partial) Autocorrelation Function] [autocorr duur cons D] [2008-12-21 17:18:56] [fad8a251ac01c156a8ae23a83577546f]
-   PD        [(Partial) Autocorrelation Function] [autocorr nt duur ...] [2008-12-21 17:22:22] [fad8a251ac01c156a8ae23a83577546f]
-   PD        [(Partial) Autocorrelation Function] [autocorr nt duur ...] [2008-12-21 17:24:42] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr inv] [2008-12-19 11:21:38] [fad8a251ac01c156a8ae23a83577546f]
-   PD      [(Partial) Autocorrelation Function] [auto corr inv] [2008-12-19 11:23:02] [fad8a251ac01c156a8ae23a83577546f]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
72,5
72,0
98,8
75,2
81,2
88,0
54,6
68,6
101,5
93,4
84,5
91,4
64,5
64,5
117,3
73,5
79,7
102,6
57,9
73,1
102,4
82,3
89,1
84,7
81,4
67,5
113,9
83,8
73,9
103,9
67,9
62,5
125,4
79,1
106,3
96,2
94,3
85,6
117,4
88,5
124,2
119,3
76,8
70,6
122,1
109,5
119,9
102,3
79,6
78,2
103,6
77,8
99,1
105,7
84,1
88,7
108,0
98,1
101,0
82,0

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32606&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32606&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32606&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
179.62512.860371949001626.8
273.114.720960113615833.4
392.76.9966658726377217
479.9525.258859831750152.8
578.32518.579984750621744.7
689.6258.9700891857327720.1
786.6519.536035080503646.4
877.0518.495675170158041.4
9101.7519.355016576243746.3
1096.4514.427404478976831.8
1197.72527.928644196714453.6
12113.459.243916918709319.8
1384.812.557069721873825.8
1494.49.8040807830209221.6
1597.27510.998598395553326

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 79.625 & 12.8603719490016 & 26.8 \tabularnewline
2 & 73.1 & 14.7209601136158 & 33.4 \tabularnewline
3 & 92.7 & 6.99666587263772 & 17 \tabularnewline
4 & 79.95 & 25.2588598317501 & 52.8 \tabularnewline
5 & 78.325 & 18.5799847506217 & 44.7 \tabularnewline
6 & 89.625 & 8.97008918573277 & 20.1 \tabularnewline
7 & 86.65 & 19.5360350805036 & 46.4 \tabularnewline
8 & 77.05 & 18.4956751701580 & 41.4 \tabularnewline
9 & 101.75 & 19.3550165762437 & 46.3 \tabularnewline
10 & 96.45 & 14.4274044789768 & 31.8 \tabularnewline
11 & 97.725 & 27.9286441967144 & 53.6 \tabularnewline
12 & 113.45 & 9.2439169187093 & 19.8 \tabularnewline
13 & 84.8 & 12.5570697218738 & 25.8 \tabularnewline
14 & 94.4 & 9.80408078302092 & 21.6 \tabularnewline
15 & 97.275 & 10.9985983955533 & 26 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32606&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]79.625[/C][C]12.8603719490016[/C][C]26.8[/C][/ROW]
[ROW][C]2[/C][C]73.1[/C][C]14.7209601136158[/C][C]33.4[/C][/ROW]
[ROW][C]3[/C][C]92.7[/C][C]6.99666587263772[/C][C]17[/C][/ROW]
[ROW][C]4[/C][C]79.95[/C][C]25.2588598317501[/C][C]52.8[/C][/ROW]
[ROW][C]5[/C][C]78.325[/C][C]18.5799847506217[/C][C]44.7[/C][/ROW]
[ROW][C]6[/C][C]89.625[/C][C]8.97008918573277[/C][C]20.1[/C][/ROW]
[ROW][C]7[/C][C]86.65[/C][C]19.5360350805036[/C][C]46.4[/C][/ROW]
[ROW][C]8[/C][C]77.05[/C][C]18.4956751701580[/C][C]41.4[/C][/ROW]
[ROW][C]9[/C][C]101.75[/C][C]19.3550165762437[/C][C]46.3[/C][/ROW]
[ROW][C]10[/C][C]96.45[/C][C]14.4274044789768[/C][C]31.8[/C][/ROW]
[ROW][C]11[/C][C]97.725[/C][C]27.9286441967144[/C][C]53.6[/C][/ROW]
[ROW][C]12[/C][C]113.45[/C][C]9.2439169187093[/C][C]19.8[/C][/ROW]
[ROW][C]13[/C][C]84.8[/C][C]12.5570697218738[/C][C]25.8[/C][/ROW]
[ROW][C]14[/C][C]94.4[/C][C]9.80408078302092[/C][C]21.6[/C][/ROW]
[ROW][C]15[/C][C]97.275[/C][C]10.9985983955533[/C][C]26[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32606&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32606&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
179.62512.860371949001626.8
273.114.720960113615833.4
392.76.9966658726377217
479.9525.258859831750152.8
578.32518.579984750621744.7
689.6258.9700891857327720.1
786.6519.536035080503646.4
877.0518.495675170158041.4
9101.7519.355016576243746.3
1096.4514.427404478976831.8
1197.72527.928644196714453.6
12113.459.243916918709319.8
1384.812.557069721873825.8
1494.49.8040807830209221.6
1597.27510.998598395553326






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha27.0154478476010
beta-0.130688518803985
S.D.0.149403691224938
T-STAT-0.874734203234804
p-value0.397591571211272

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 27.0154478476010 \tabularnewline
beta & -0.130688518803985 \tabularnewline
S.D. & 0.149403691224938 \tabularnewline
T-STAT & -0.874734203234804 \tabularnewline
p-value & 0.397591571211272 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32606&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]27.0154478476010[/C][/ROW]
[ROW][C]beta[/C][C]-0.130688518803985[/C][/ROW]
[ROW][C]S.D.[/C][C]0.149403691224938[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.874734203234804[/C][/ROW]
[ROW][C]p-value[/C][C]0.397591571211272[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32606&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32606&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)
alpha27.0154478476010
beta-0.130688518803985
S.D.0.149403691224938
T-STAT-0.874734203234804
p-value0.397591571211272






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.1362057845477
beta-0.998655894067462
S.D.0.870264256021146
T-STAT-1.14753178377488
p-value0.271842198359207
Lambda1.99865589406746

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.1362057845477 \tabularnewline
beta & -0.998655894067462 \tabularnewline
S.D. & 0.870264256021146 \tabularnewline
T-STAT & -1.14753178377488 \tabularnewline
p-value & 0.271842198359207 \tabularnewline
Lambda & 1.99865589406746 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32606&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.1362057845477[/C][/ROW]
[ROW][C]beta[/C][C]-0.998655894067462[/C][/ROW]
[ROW][C]S.D.[/C][C]0.870264256021146[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.14753178377488[/C][/ROW]
[ROW][C]p-value[/C][C]0.271842198359207[/C][/ROW]
[ROW][C]Lambda[/C][C]1.99865589406746[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32606&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32606&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)
alpha7.1362057845477
beta-0.998655894067462
S.D.0.870264256021146
T-STAT-1.14753178377488
p-value0.271842198359207
Lambda1.99865589406746


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')