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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 computationThu, 11 Dec 2008 10:40:25 -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/11/t12290172532fp87cryp2f8rf3.htm/, Retrieved Sun, 19 May 2024 07:08:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32390, Retrieved Sun, 19 May 2024 07:08:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

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] [Werkloosheid 50 e...] [2008-11-28 13:15:36] [6743688719638b0cb1c0a6e0bf433315]
-   P   [Univariate Data Series] [Unemployment from...] [2008-12-02 18:04:33] [6743688719638b0cb1c0a6e0bf433315]
- RMP     [Variance Reduction Matrix] [unemployment abov...] [2008-12-03 16:43:35] [6743688719638b0cb1c0a6e0bf433315]
- RM          [Standard Deviation-Mean Plot] [lambda] [2008-12-11 17:40:25] [9b05d7ef5dbcfba4217d280d9092f628] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
44028
45564
44277
44976
45406
47379
49200
50221
51573
53091
53337
54978
57885
67099
67169
69796
70600
71982
73957
75273
76322
77078
77954
79238
82179
83834
83744
84861
86478
88290
90287
91230
92380
92506
94172
94728
96581
97344
98346
98214
98366
98768
99832
99976
99961
100164
99964
99304
104008
104644
103950
104263
104241
105141
106018
105866
105944
106379
105082
104915
107026

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32390&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]4 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=32390&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32390&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
148669.16666666673916.0596808836310950
272029.41666666676032.0812699241521353
388724.08333333334408.9449461156612549
498901.66666666671164.789667578223583
5105037.583333333848.982648750132429

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 48669.1666666667 & 3916.05968088363 & 10950 \tabularnewline
2 & 72029.4166666667 & 6032.08126992415 & 21353 \tabularnewline
3 & 88724.0833333333 & 4408.94494611566 & 12549 \tabularnewline
4 & 98901.6666666667 & 1164.78966757822 & 3583 \tabularnewline
5 & 105037.583333333 & 848.98264875013 & 2429 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32390&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]48669.1666666667[/C][C]3916.05968088363[/C][C]10950[/C][/ROW]
[ROW][C]2[/C][C]72029.4166666667[/C][C]6032.08126992415[/C][C]21353[/C][/ROW]
[ROW][C]3[/C][C]88724.0833333333[/C][C]4408.94494611566[/C][C]12549[/C][/ROW]
[ROW][C]4[/C][C]98901.6666666667[/C][C]1164.78966757822[/C][C]3583[/C][/ROW]
[ROW][C]5[/C][C]105037.583333333[/C][C]848.98264875013[/C][C]2429[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32390&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32390&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
148669.16666666673916.0596808836310950
272029.41666666676032.0812699241521353
388724.08333333334408.9449461156612549
498901.66666666671164.789667578223583
5105037.583333333848.982648750132429






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8578.13317331618
beta-0.0641563883465215
S.D.0.0423150686028328
T-STAT-1.51615938399369
p-value0.226740672951239

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8578.13317331618 \tabularnewline
beta & -0.0641563883465215 \tabularnewline
S.D. & 0.0423150686028328 \tabularnewline
T-STAT & -1.51615938399369 \tabularnewline
p-value & 0.226740672951239 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32390&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8578.13317331618[/C][/ROW]
[ROW][C]beta[/C][C]-0.0641563883465215[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0423150686028328[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.51615938399369[/C][/ROW]
[ROW][C]p-value[/C][C]0.226740672951239[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32390&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32390&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)
alpha8578.13317331618
beta-0.0641563883465215
S.D.0.0423150686028328
T-STAT-1.51615938399369
p-value0.226740672951239






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha28.5769335627277
beta-1.83771575206394
S.D.1.22243873521778
T-STAT-1.50331930682525
p-value0.229788627069311
Lambda2.83771575206394

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 28.5769335627277 \tabularnewline
beta & -1.83771575206394 \tabularnewline
S.D. & 1.22243873521778 \tabularnewline
T-STAT & -1.50331930682525 \tabularnewline
p-value & 0.229788627069311 \tabularnewline
Lambda & 2.83771575206394 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32390&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]28.5769335627277[/C][/ROW]
[ROW][C]beta[/C][C]-1.83771575206394[/C][/ROW]
[ROW][C]S.D.[/C][C]1.22243873521778[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.50331930682525[/C][/ROW]
[ROW][C]p-value[/C][C]0.229788627069311[/C][/ROW]
[ROW][C]Lambda[/C][C]2.83771575206394[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32390&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32390&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)
alpha28.5769335627277
beta-1.83771575206394
S.D.1.22243873521778
T-STAT-1.50331930682525
p-value0.229788627069311
Lambda2.83771575206394


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')