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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 computationMon, 08 Dec 2008 15:45:41 -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/08/t1228776492w4wi6dlydkiee0b.htm/, Retrieved Thu, 16 May 2024 20:29:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31106, Retrieved Thu, 16 May 2024 20:29:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact208

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [] [2008-12-01 19:22:35] [2a0ad3a9bcadca2da0acb91636601c6c]
-   P   [(Partial) Autocorrelation Function] [] [2008-12-01 19:27:13] [2a0ad3a9bcadca2da0acb91636601c6c]
- RMPD    [Standard Deviation-Mean Plot] [SD Mean Bouwprodu...] [2008-12-08 22:32:48] [aa5573c1db401b164e448aef050955a1]
F             [Standard Deviation-Mean Plot] [SD Mean Bouwprodu...] [2008-12-08 22:45:41] [75bb900725b62536e5118c999dc0ce41] [Current]
F RM            [Variance Reduction Matrix] [VRM Bouwproductie] [2008-12-08 22:57:37] [aa5573c1db401b164e448aef050955a1]
F RM              [(Partial) Autocorrelation Function] [PACF bouwproducti...] [2008-12-08 23:26:01] [aa5573c1db401b164e448aef050955a1]
F                   [(Partial) Autocorrelation Function] [PACF bouwproducti...] [2008-12-08 23:39:37] [aa5573c1db401b164e448aef050955a1]
F RM                [Spectral Analysis] [Spectrum analyse ...] [2008-12-08 23:49:25] [aa5573c1db401b164e448aef050955a1]
F                     [Spectral Analysis] [Spectrum analyse ...] [2008-12-08 23:53:38] [aa5573c1db401b164e448aef050955a1]
Feedback Forum
2008-12-14 13:12:25 [Jeroen Michel] [reply] 
Ook hier stelt de student duidelijk hoe de data, grafieken, en tabellen moeten worden afgelezen. Op die manier kan de lezer van dit werk meteen de resultaten interpreteren. Ook hier hangt dus een zeer uitgebreide analyse aan vast.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3
99.4
85.9
109.4
97.6

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 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=31106&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]3 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=31106&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31106&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
192.758333333333316.10174797588154.6
291.716666666666716.727105565699760.3
388.066666666666717.739495397831864.7
490.683333333333318.109055159998862.4
593.166666666666717.18552950136963.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 92.7583333333333 & 16.101747975881 & 54.6 \tabularnewline
2 & 91.7166666666667 & 16.7271055656997 & 60.3 \tabularnewline
3 & 88.0666666666667 & 17.7394953978318 & 64.7 \tabularnewline
4 & 90.6833333333333 & 18.1090551599988 & 62.4 \tabularnewline
5 & 93.1666666666667 & 17.185529501369 & 63.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31106&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]92.7583333333333[/C][C]16.101747975881[/C][C]54.6[/C][/ROW]
[ROW][C]2[/C][C]91.7166666666667[/C][C]16.7271055656997[/C][C]60.3[/C][/ROW]
[ROW][C]3[/C][C]88.0666666666667[/C][C]17.7394953978318[/C][C]64.7[/C][/ROW]
[ROW][C]4[/C][C]90.6833333333333[/C][C]18.1090551599988[/C][C]62.4[/C][/ROW]
[ROW][C]5[/C][C]93.1666666666667[/C][C]17.185529501369[/C][C]63.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31106&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31106&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
192.758333333333316.10174797588154.6
291.716666666666716.727105565699760.3
388.066666666666717.739495397831864.7
490.683333333333318.109055159998862.4
593.166666666666717.18552950136963.2






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha39.8784594614256
beta-0.248754243335616
S.D.0.174352583679079
T-STAT-1.42673104170044
p-value0.248926256845786

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 39.8784594614256 \tabularnewline
beta & -0.248754243335616 \tabularnewline
S.D. & 0.174352583679079 \tabularnewline
T-STAT & -1.42673104170044 \tabularnewline
p-value & 0.248926256845786 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31106&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]39.8784594614256[/C][/ROW]
[ROW][C]beta[/C][C]-0.248754243335616[/C][/ROW]
[ROW][C]S.D.[/C][C]0.174352583679079[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.42673104170044[/C][/ROW]
[ROW][C]p-value[/C][C]0.248926256845786[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31106&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31106&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)
alpha39.8784594614256
beta-0.248754243335616
S.D.0.174352583679079
T-STAT-1.42673104170044
p-value0.248926256845786






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha8.76174595071043
beta-1.31140395864577
S.D.0.92682059451698
T-STAT-1.41494909198605
p-value0.252020928335136
Lambda2.31140395864577

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 8.76174595071043 \tabularnewline
beta & -1.31140395864577 \tabularnewline
S.D. & 0.92682059451698 \tabularnewline
T-STAT & -1.41494909198605 \tabularnewline
p-value & 0.252020928335136 \tabularnewline
Lambda & 2.31140395864577 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31106&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.76174595071043[/C][/ROW]
[ROW][C]beta[/C][C]-1.31140395864577[/C][/ROW]
[ROW][C]S.D.[/C][C]0.92682059451698[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.41494909198605[/C][/ROW]
[ROW][C]p-value[/C][C]0.252020928335136[/C][/ROW]
[ROW][C]Lambda[/C][C]2.31140395864577[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31106&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31106&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)
alpha8.76174595071043
beta-1.31140395864577
S.D.0.92682059451698
T-STAT-1.41494909198605
p-value0.252020928335136
Lambda2.31140395864577


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.0 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 0.0 ; par6 = 1 ; par7 = 0 ;
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')