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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 11 Aug 2016 01:08:38 +0100

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/2016/Aug/11/t1470874202oqcxgjck4gl4bmo.htm/, Retrieved Sun, 05 May 2024 13:06:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296285, Retrieved Sun, 05 May 2024 13:06:42 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

102

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Standard Deviation-Mean Plot] [] [2016-08-11 00:08:38] [dce1b7f6243247e331d0750a8103b593] [Current]

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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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296285&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296285&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296285&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	910.833333333333	48.3281083905222	160
2	927.5	91.663911804334	340
3	920.833333333333	117.1214081303	430
4	913.333333333333	125.722156384866	400
5	912.5	160.347633709898	510
6	911.666666666667	140.637078605849	370
7	945.833333333333	163.399028223066	440
8	925.833333333333	166.212259329795	490
9	928.333333333333	155.436823374019	520

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 910.833333333333 & 48.3281083905222 & 160 \tabularnewline
2 & 927.5 & 91.663911804334 & 340 \tabularnewline
3 & 920.833333333333 & 117.1214081303 & 430 \tabularnewline
4 & 913.333333333333 & 125.722156384866 & 400 \tabularnewline
5 & 912.5 & 160.347633709898 & 510 \tabularnewline
6 & 911.666666666667 & 140.637078605849 & 370 \tabularnewline
7 & 945.833333333333 & 163.399028223066 & 440 \tabularnewline
8 & 925.833333333333 & 166.212259329795 & 490 \tabularnewline
9 & 928.333333333333 & 155.436823374019 & 520 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296285&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]910.833333333333[/C][C]48.3281083905222[/C][C]160[/C][/ROW]
[ROW][C]2[/C][C]927.5[/C][C]91.663911804334[/C][C]340[/C][/ROW]
[ROW][C]3[/C][C]920.833333333333[/C][C]117.1214081303[/C][C]430[/C][/ROW]
[ROW][C]4[/C][C]913.333333333333[/C][C]125.722156384866[/C][C]400[/C][/ROW]
[ROW][C]5[/C][C]912.5[/C][C]160.347633709898[/C][C]510[/C][/ROW]
[ROW][C]6[/C][C]911.666666666667[/C][C]140.637078605849[/C][C]370[/C][/ROW]
[ROW][C]7[/C][C]945.833333333333[/C][C]163.399028223066[/C][C]440[/C][/ROW]
[ROW][C]8[/C][C]925.833333333333[/C][C]166.212259329795[/C][C]490[/C][/ROW]
[ROW][C]9[/C][C]928.333333333333[/C][C]155.436823374019[/C][C]520[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296285&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296285&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	910.833333333333	48.3281083905222	160
2	927.5	91.663911804334	340
3	920.833333333333	117.1214081303	430
4	913.333333333333	125.722156384866	400
5	912.5	160.347633709898	510
6	911.666666666667	140.637078605849	370
7	945.833333333333	163.399028223066	440
8	925.833333333333	166.212259329795	490
9	928.333333333333	155.436823374019	520

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-1142.5446707739
beta	1.3802857105164
S.D.	1.19059382885874
T-STAT	1.15932543665164
p-value	0.284336677029027

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1142.5446707739 \tabularnewline
beta & 1.3802857105164 \tabularnewline
S.D. & 1.19059382885874 \tabularnewline
T-STAT & 1.15932543665164 \tabularnewline
p-value & 0.284336677029027 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296285&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1142.5446707739[/C][/ROW]
[ROW][C]beta[/C][C]1.3802857105164[/C][/ROW]
[ROW][C]S.D.[/C][C]1.19059382885874[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.15932543665164[/C][/ROW]
[ROW][C]p-value[/C][C]0.284336677029027[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296285&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296285&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	-1142.5446707739
beta	1.3802857105164
S.D.	1.19059382885874
T-STAT	1.15932543665164
p-value	0.284336677029027

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-80.6635871049896
beta	12.5209052904113
S.D.	11.2503470773501
T-STAT	1.11293502363311
p-value	0.302489256378107
Lambda	-11.5209052904113

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -80.6635871049896 \tabularnewline
beta & 12.5209052904113 \tabularnewline
S.D. & 11.2503470773501 \tabularnewline
T-STAT & 1.11293502363311 \tabularnewline
p-value & 0.302489256378107 \tabularnewline
Lambda & -11.5209052904113 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296285&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-80.6635871049896[/C][/ROW]
[ROW][C]beta[/C][C]12.5209052904113[/C][/ROW]
[ROW][C]S.D.[/C][C]11.2503470773501[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11293502363311[/C][/ROW]
[ROW][C]p-value[/C][C]0.302489256378107[/C][/ROW]
[ROW][C]Lambda[/C][C]-11.5209052904113[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296285&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296285&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	-80.6635871049896
beta	12.5209052904113
S.D.	11.2503470773501
T-STAT	1.11293502363311
p-value	0.302489256378107
Lambda	-11.5209052904113

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