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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, 07 Dec 2011 09:22:28 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/07/t1323267842ewdk8i3m1m8620n.htm/, Retrieved Thu, 02 May 2024 18:07:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152432, Retrieved Thu, 02 May 2024 18:07:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

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] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R  D    [(Partial) Autocorrelation Function] [autocorrelatie ] [2011-12-07 13:35:25] [141ef847e2c5f8e947fe4eabcb0cf143]
-   PD      [(Partial) Autocorrelation Function] [autocorrelatie D=1] [2011-12-07 13:50:51] [141ef847e2c5f8e947fe4eabcb0cf143]
- RMP           [Standard Deviation-Mean Plot] [ST-MP] [2011-12-07 14:22:28] [1a4698f17d8e7f554418314cf0e4bd67] [Current]
- RMP             [ARIMA Backward Selection] [ARIMA backward ] [2011-12-08 13:48:01] [141ef847e2c5f8e947fe4eabcb0cf143]
- R                 [ARIMA Backward Selection] [ARIMA backward nieuw] [2011-12-08 14:12:51] [141ef847e2c5f8e947fe4eabcb0cf143]
- RM                [ARIMA Forecasting] [ARIMA forecasting...] [2011-12-08 14:14:36] [141ef847e2c5f8e947fe4eabcb0cf143]
- R P                 [ARIMA Forecasting] [Arima forecasting...] [2011-12-21 11:37:56] [141ef847e2c5f8e947fe4eabcb0cf143]
- R P               [ARIMA Backward Selection] [ARIMA backward nieuw] [2011-12-19 19:26:36] [141ef847e2c5f8e947fe4eabcb0cf143]
- RMPD                [Skewness and Kurtosis Test] [skewness] [2011-12-22 14:43:07] [141ef847e2c5f8e947fe4eabcb0cf143]
- RMPD                [Central Tendency] [gemiddelde] [2011-12-22 15:14:40] [141ef847e2c5f8e947fe4eabcb0cf143]
- RMPD                [Central Tendency] [gemiddelde] [2011-12-22 23:25:55] [141ef847e2c5f8e947fe4eabcb0cf143]
- RMPD                [Skewness and Kurtosis Test] [kurtosis en skewness] [2011-12-22 23:27:30] [141ef847e2c5f8e947fe4eabcb0cf143]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114.7
108
101.3
108.4
105.6
120.4
107.6
111.4
122.1
104.8
103.2
112.3
123.1
115.5
106.3
119.9
119.5
120.9
127.5
116.6
126.7
110.6
100.4
125.2
125
105.2
102.7
94.2
97
111.1
102
97.3
109.8
98.9
93.2
115.2
115
107
104.1
106
110.8
127.8
116.9
113.8
131.6
106.1
107.2
127.4
123
121.8
117.6
118.4
121.8
141.9
122.1
132.2
131.6
108.8
120.4
134.7

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'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152432&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152432&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152432&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1109.9833333333336.4986478780146520.8
2117.6833333333338.347436550803927.1
3104.39.4826156729037631.8
4114.4759.612503694289427.5
5124.5258.9808002275561633.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 109.983333333333 & 6.49864787801465 & 20.8 \tabularnewline
2 & 117.683333333333 & 8.3474365508039 & 27.1 \tabularnewline
3 & 104.3 & 9.48261567290376 & 31.8 \tabularnewline
4 & 114.475 & 9.6125036942894 & 27.5 \tabularnewline
5 & 124.525 & 8.98080022755616 & 33.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152432&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]109.983333333333[/C][C]6.49864787801465[/C][C]20.8[/C][/ROW]
[ROW][C]2[/C][C]117.683333333333[/C][C]8.3474365508039[/C][C]27.1[/C][/ROW]
[ROW][C]3[/C][C]104.3[/C][C]9.48261567290376[/C][C]31.8[/C][/ROW]
[ROW][C]4[/C][C]114.475[/C][C]9.6125036942894[/C][C]27.5[/C][/ROW]
[ROW][C]5[/C][C]124.525[/C][C]8.98080022755616[/C][C]33.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152432&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152432&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
1109.9833333333336.4986478780146520.8
2117.6833333333338.347436550803927.1
3104.39.4826156729037631.8
4114.4759.612503694289427.5
5124.5258.9808002275561633.1






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.90379613120398
beta0.0147171872862654
S.D.0.0951844748954278
T-STAT0.154617518271063
p-value0.886939388985412

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.90379613120398 \tabularnewline
beta & 0.0147171872862654 \tabularnewline
S.D. & 0.0951844748954278 \tabularnewline
T-STAT & 0.154617518271063 \tabularnewline
p-value & 0.886939388985412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152432&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.90379613120398[/C][/ROW]
[ROW][C]beta[/C][C]0.0147171872862654[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0951844748954278[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.154617518271063[/C][/ROW]
[ROW][C]p-value[/C][C]0.886939388985412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152432&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152432&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)
alpha6.90379613120398
beta0.0147171872862654
S.D.0.0951844748954278
T-STAT0.154617518271063
p-value0.886939388985412






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.905988876500637
beta0.260603805950481
S.D.1.36886190312525
T-STAT0.190379910022696
p-value0.861165820602051
Lambda0.739396194049519

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.905988876500637 \tabularnewline
beta & 0.260603805950481 \tabularnewline
S.D. & 1.36886190312525 \tabularnewline
T-STAT & 0.190379910022696 \tabularnewline
p-value & 0.861165820602051 \tabularnewline
Lambda & 0.739396194049519 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152432&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.905988876500637[/C][/ROW]
[ROW][C]beta[/C][C]0.260603805950481[/C][/ROW]
[ROW][C]S.D.[/C][C]1.36886190312525[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.190379910022696[/C][/ROW]
[ROW][C]p-value[/C][C]0.861165820602051[/C][/ROW]
[ROW][C]Lambda[/C][C]0.739396194049519[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152432&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152432&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)
alpha0.905988876500637
beta0.260603805950481
S.D.1.36886190312525
T-STAT0.190379910022696
p-value0.861165820602051
Lambda0.739396194049519


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')