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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 28 Dec 2010 15:54:33 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/28/t12935515601qt09dh3k9d9k3c.htm/, Retrieved Sun, 05 May 2024 00:21:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116393, Retrieved Sun, 05 May 2024 00:21:26 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

117

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   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   PD    [Standard Deviation-Mean Plot] [] [2010-12-14 14:07:24] [897115520fe7b6114489bc0eeed64548]
-           [Standard Deviation-Mean Plot] [] [2010-12-14 19:16:51] [f9d37301ea08122b4d103fe011f2b292]
-    D          [Standard Deviation-Mean Plot] [standaard deviati...] [2010-12-28 15:54:33] [ea05999e24dc6223e14cc730e7a15b1e] [Current]

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Dataseries X:

Download CSV

Histogram

Boxplots

9119000
9166000
9218000
9283000
9367000
9448000
9508000
9557000
9590000
9613000
9638000
9673000
9709000
9738000
9768000
9795000
9811000
9822000
9830000
9837000
9847000
9852000
9856000
9856000
9853000
9858000
9862000
9870000
9902000
9938000
9967400
10004500
10045000
10084500
10115600
10136800
10157000
10181000
10203000
10226000
10252000
10287000
10333000
10376080,14
10421120,61
10478650
10547958
10625700
10708433
10788760

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=116393&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=116393&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116393&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	9431666.66666667	195598.072742566	554000
2	9810083.33333333	48629.3183795599	147000
3	9969733.33333333	105528.112009277	283800
4	10340709.0625	151689.916635473	468700

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9431666.66666667 & 195598.072742566 & 554000 \tabularnewline
2 & 9810083.33333333 & 48629.3183795599 & 147000 \tabularnewline
3 & 9969733.33333333 & 105528.112009277 & 283800 \tabularnewline
4 & 10340709.0625 & 151689.916635473 & 468700 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116393&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]9431666.66666667[/C][C]195598.072742566[/C][C]554000[/C][/ROW]
[ROW][C]2[/C][C]9810083.33333333[/C][C]48629.3183795599[/C][C]147000[/C][/ROW]
[ROW][C]3[/C][C]9969733.33333333[/C][C]105528.112009277[/C][C]283800[/C][/ROW]
[ROW][C]4[/C][C]10340709.0625[/C][C]151689.916635473[/C][C]468700[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116393&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116393&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	9431666.66666667	195598.072742566	554000
2	9810083.33333333	48629.3183795599	147000
3	9969733.33333333	105528.112009277	283800
4	10340709.0625	151689.916635473	468700

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	491563.706718461
beta	-0.0370348473340577
S.D.	0.115292150166567
T-STAT	-0.321226096317504
p-value	0.778500904175186

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 491563.706718461 \tabularnewline
beta & -0.0370348473340577 \tabularnewline
S.D. & 0.115292150166567 \tabularnewline
T-STAT & -0.321226096317504 \tabularnewline
p-value & 0.778500904175186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116393&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]491563.706718461[/C][/ROW]
[ROW][C]beta[/C][C]-0.0370348473340577[/C][/ROW]
[ROW][C]S.D.[/C][C]0.115292150166567[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.321226096317504[/C][/ROW]
[ROW][C]p-value[/C][C]0.778500904175186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116393&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116393&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	491563.706718461
beta	-0.0370348473340577
S.D.	0.115292150166567
T-STAT	-0.321226096317504
p-value	0.778500904175186

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	36.235088285165
beta	-1.52841242978560
S.D.	11.1831577059233
T-STAT	-0.136670917998059
p-value	0.903807217948442
Lambda	2.52841242978559

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 36.235088285165 \tabularnewline
beta & -1.52841242978560 \tabularnewline
S.D. & 11.1831577059233 \tabularnewline
T-STAT & -0.136670917998059 \tabularnewline
p-value & 0.903807217948442 \tabularnewline
Lambda & 2.52841242978559 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116393&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]36.235088285165[/C][/ROW]
[ROW][C]beta[/C][C]-1.52841242978560[/C][/ROW]
[ROW][C]S.D.[/C][C]11.1831577059233[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.136670917998059[/C][/ROW]
[ROW][C]p-value[/C][C]0.903807217948442[/C][/ROW]
[ROW][C]Lambda[/C][C]2.52841242978559[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116393&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116393&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	36.235088285165
beta	-1.52841242978560
S.D.	11.1831577059233
T-STAT	-0.136670917998059
p-value	0.903807217948442
Lambda	2.52841242978559

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code