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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 computationSat, 12 Dec 2009 08:28:35 -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/12/t1260631771fndii8dwbw1h7hd.htm/, Retrieved Mon, 29 Apr 2024 08:17:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67018, Retrieved Mon, 29 Apr 2024 08:17:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [Paper] [2009-12-12 13:34:31] [d31db4f83c6a129f6d3e47077769e868]
-    D  [Bivariate Kernel Density Estimation] [Paper.1] [2009-12-12 13:38:38] [d31db4f83c6a129f6d3e47077769e868]
- RMPD    [Standard Deviation-Mean Plot] [Paper. Mean Plot ...] [2009-12-12 14:46:45] [d31db4f83c6a129f6d3e47077769e868]
-    D      [Standard Deviation-Mean Plot] [Paper] [2009-12-12 14:54:21] [d31db4f83c6a129f6d3e47077769e868]
-    D          [Standard Deviation-Mean Plot] [Paper. Ingeschrev...] [2009-12-12 15:28:35] [852eae237d08746109043531619a60c9] [Current]
-    D            [Standard Deviation-Mean Plot] [Paper. achtergest...] [2009-12-12 15:31:03] [d31db4f83c6a129f6d3e47077769e868]
- RM D              [(Partial) Autocorrelation Function] [Paper, Partiële ...] [2009-12-12 15:59:27] [d31db4f83c6a129f6d3e47077769e868]
- RM D              [Spectral Analysis] [Paper. Spectral A...] [2009-12-12 16:10:11] [d31db4f83c6a129f6d3e47077769e868]
-   P                 [Spectral Analysis] [Paper. Spectral A...] [2009-12-18 15:52:57] [d31db4f83c6a129f6d3e47077769e868]
-   P                   [Spectral Analysis] [Paper. Spectral A...] [2009-12-18 17:24:57] [d31db4f83c6a129f6d3e47077769e868]
-   P                     [Spectral Analysis] [Paper] [2010-01-07 15:25:28] [309ee52d0058ff0a6f7eec15e07b2d9f]
- RM D              [Mean Plot] [Paper. Mean plot] [2009-12-12 16:13:07] [d31db4f83c6a129f6d3e47077769e868]
-    D                [Mean Plot] [Paper. Mean plot ...] [2009-12-12 16:15:50] [d31db4f83c6a129f6d3e47077769e868]
-    D                [Mean Plot] [Paper. Inschrijvi...] [2009-12-12 16:18:27] [d31db4f83c6a129f6d3e47077769e868]
-    D                  [Mean Plot] [Paper. Mean plot ...] [2009-12-12 16:20:40] [d31db4f83c6a129f6d3e47077769e868]
- RM D                  [ARIMA Backward Selection] [Paper. Arima back...] [2009-12-12 17:23:23] [d31db4f83c6a129f6d3e47077769e868]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
18  004
17  537
20  366
22  782
19  169
13  807
29  743
25  591
29  096
26  482
22  405
27  044
17  970
18  730
19  684
19  785
18  479
10  698
31  956
29  506
34  506
27  165
26  736
23  691
18  157
17  328
18  205
20  995
17  382
9  367
31  124
26  551
30  651
25  859
25  100
25  778
20  418
18  688
20  424
24  776
19  814
12  738
31  566
30  111
30  019
31  934
25  826
26  835
20  205
17  789
20  520
22  518
15  572
11  509
25  447
24  090
27  786
26  195
20  516
22  759
19  028

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=67018&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=67018&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67018&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
122668.83333333335025.7197554784215936
223242.16666666676893.0083132156923808
322208.08333333336395.8882737744921757
424429.08333333336043.1840261771319196
521242.16666666674651.5477938840816277

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22668.8333333333 & 5025.71975547842 & 15936 \tabularnewline
2 & 23242.1666666667 & 6893.00831321569 & 23808 \tabularnewline
3 & 22208.0833333333 & 6395.88827377449 & 21757 \tabularnewline
4 & 24429.0833333333 & 6043.18402617713 & 19196 \tabularnewline
5 & 21242.1666666667 & 4651.54779388408 & 16277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67018&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]22668.8333333333[/C][C]5025.71975547842[/C][C]15936[/C][/ROW]
[ROW][C]2[/C][C]23242.1666666667[/C][C]6893.00831321569[/C][C]23808[/C][/ROW]
[ROW][C]3[/C][C]22208.0833333333[/C][C]6395.88827377449[/C][C]21757[/C][/ROW]
[ROW][C]4[/C][C]24429.0833333333[/C][C]6043.18402617713[/C][C]19196[/C][/ROW]
[ROW][C]5[/C][C]21242.1666666667[/C][C]4651.54779388408[/C][C]16277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67018&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67018&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
122668.83333333335025.7197554784215936
223242.16666666676893.0083132156923808
322208.08333333336395.8882737744921757
424429.08333333336043.1840261771319196
521242.16666666674651.5477938840816277






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-3962.78112264399
beta0.429063281084947
S.D.0.38378223286928
T-STAT1.11798630665399
p-value0.345032225755363

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3962.78112264399 \tabularnewline
beta & 0.429063281084947 \tabularnewline
S.D. & 0.38378223286928 \tabularnewline
T-STAT & 1.11798630665399 \tabularnewline
p-value & 0.345032225755363 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67018&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3962.78112264399[/C][/ROW]
[ROW][C]beta[/C][C]0.429063281084947[/C][/ROW]
[ROW][C]S.D.[/C][C]0.38378223286928[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11798630665399[/C][/ROW]
[ROW][C]p-value[/C][C]0.345032225755363[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67018&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67018&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)
alpha-3962.78112264399
beta0.429063281084947
S.D.0.38378223286928
T-STAT1.11798630665399
p-value0.345032225755363






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.76023899972568
beta1.83573742326266
S.D.1.50208622936639
T-STAT1.22212519319680
p-value0.308925114608067
Lambda-0.83573742326266

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.76023899972568 \tabularnewline
beta & 1.83573742326266 \tabularnewline
S.D. & 1.50208622936639 \tabularnewline
T-STAT & 1.22212519319680 \tabularnewline
p-value & 0.308925114608067 \tabularnewline
Lambda & -0.83573742326266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67018&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.76023899972568[/C][/ROW]
[ROW][C]beta[/C][C]1.83573742326266[/C][/ROW]
[ROW][C]S.D.[/C][C]1.50208622936639[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.22212519319680[/C][/ROW]
[ROW][C]p-value[/C][C]0.308925114608067[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.83573742326266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67018&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67018&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)
alpha-9.76023899972568
beta1.83573742326266
S.D.1.50208622936639
T-STAT1.22212519319680
p-value0.308925114608067
Lambda-0.83573742326266


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')