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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 computationWed, 30 Dec 2009 04:32:10 -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/2009/Dec/30/t1262173244xikwnxlu4cbsfvy.htm/, Retrieved Sun, 28 Apr 2024 22:51:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71251, Retrieved Sun, 28 Apr 2024 22:51:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [De Belgische uitv...] [2009-10-13 01:35:54] [df6326eec97a6ca984a853b142930499]
- RMPD  [Univariate Data Series] [ws8] [2009-11-27 12:04:12] [acdebb2ecda2ddb208f4e14f4a68b9e7]
-   PD    [Univariate Data Series] [consumptiekrediet] [2009-12-04 10:09:44] [acdebb2ecda2ddb208f4e14f4a68b9e7]
-   PD      [Univariate Data Series] [Verkoopprijs per ...] [2009-12-20 19:05:51] [acdebb2ecda2ddb208f4e14f4a68b9e7]
- RMPD          [Standard Deviation-Mean Plot] [] [2009-12-30 11:32:10] [b243db81ea3e1f02fb3382887fb0f701] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
228
136
174
69
108
149
134
131
180
127
59
59
202
173
296
154
117
86
38
17
52
12
61
65
70
91
111
90
110
100
99
137
139
124
103
75
55
75
65
17
27
17
20
131
26
66
59
35
57
6
24
57
42
55
30
35
22
18
22
82
90
66
64
50
56
99
97
41
59
92
91
47

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71251&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71251&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1129.551.1210684196216169
2106.08333333333385.6169676612945284
3104.08333333333321.748389003381969
449.416666666666733.2714956718574114
537.521.668997543621076
67121.366924311782858

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 129.5 & 51.1210684196216 & 169 \tabularnewline
2 & 106.083333333333 & 85.6169676612945 & 284 \tabularnewline
3 & 104.083333333333 & 21.7483890033819 & 69 \tabularnewline
4 & 49.4166666666667 & 33.2714956718574 & 114 \tabularnewline
5 & 37.5 & 21.6689975436210 & 76 \tabularnewline
6 & 71 & 21.3669243117828 & 58 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71251&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]129.5[/C][C]51.1210684196216[/C][C]169[/C][/ROW]
[ROW][C]2[/C][C]106.083333333333[/C][C]85.6169676612945[/C][C]284[/C][/ROW]
[ROW][C]3[/C][C]104.083333333333[/C][C]21.7483890033819[/C][C]69[/C][/ROW]
[ROW][C]4[/C][C]49.4166666666667[/C][C]33.2714956718574[/C][C]114[/C][/ROW]
[ROW][C]5[/C][C]37.5[/C][C]21.6689975436210[/C][C]76[/C][/ROW]
[ROW][C]6[/C][C]71[/C][C]21.3669243117828[/C][C]58[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71251&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
1129.551.1210684196216169
2106.08333333333385.6169676612945284
3104.08333333333321.748389003381969
449.416666666666733.2714956718574114
537.521.668997543621076
67121.366924311782858






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha7.54771276008735
beta0.380855935791731
S.D.0.299234692112343
T-STAT1.27276664715315
p-value0.272047373025901

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 7.54771276008735 \tabularnewline
beta & 0.380855935791731 \tabularnewline
S.D. & 0.299234692112343 \tabularnewline
T-STAT & 1.27276664715315 \tabularnewline
p-value & 0.272047373025901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71251&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.54771276008735[/C][/ROW]
[ROW][C]beta[/C][C]0.380855935791731[/C][/ROW]
[ROW][C]S.D.[/C][C]0.299234692112343[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.27276664715315[/C][/ROW]
[ROW][C]p-value[/C][C]0.272047373025901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71251&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71251&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)
alpha7.54771276008735
beta0.380855935791731
S.D.0.299234692112343
T-STAT1.27276664715315
p-value0.272047373025901






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.797234900314882
beta0.628751262734051
S.D.0.497245607415463
T-STAT1.26446820918563
p-value0.274719884565775
Lambda0.371248737265949

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.797234900314882 \tabularnewline
beta & 0.628751262734051 \tabularnewline
S.D. & 0.497245607415463 \tabularnewline
T-STAT & 1.26446820918563 \tabularnewline
p-value & 0.274719884565775 \tabularnewline
Lambda & 0.371248737265949 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71251&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.797234900314882[/C][/ROW]
[ROW][C]beta[/C][C]0.628751262734051[/C][/ROW]
[ROW][C]S.D.[/C][C]0.497245607415463[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.26446820918563[/C][/ROW]
[ROW][C]p-value[/C][C]0.274719884565775[/C][/ROW]
[ROW][C]Lambda[/C][C]0.371248737265949[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71251&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71251&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)
alpha0.797234900314882
beta0.628751262734051
S.D.0.497245607415463
T-STAT1.26446820918563
p-value0.274719884565775
Lambda0.371248737265949


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')