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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

Wed, 21 Dec 2016 16:20:20 +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/Dec/21/t1482333708oj35a8ivxxypjrt.htm/, Retrieved Tue, 07 May 2024 00:11:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302378, Retrieved Tue, 07 May 2024 00:11:10 +0000

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Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2016-12-21 15:20:20] [361c8dad91b3f1ef2e651cd04783c23b] [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	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302378&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302378&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302378&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	Big Analytics Cloud Computing Center

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	4600	867.947771086103	1600
2	4725	950	2100
3	5250	1470.82743152735	3300
4	5750	2600.6409466386	5900
5	4450	1634.01346383682	3600
6	3775	1519.59424408842	3500
7	3700	1564.18242755334	3600
8	3500	1388.04418757713	3300
9	3625	1800.69431053691	4200
10	3250	1613.48484137079	3700
11	4200	1061.44555520604	2500
12	3875	1297.11217710728	2700
13	4025	2028.75166871979	4400
14	4800	1503.32963783729	2700
15	4275	1450	3200

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4600 & 867.947771086103 & 1600 \tabularnewline
2 & 4725 & 950 & 2100 \tabularnewline
3 & 5250 & 1470.82743152735 & 3300 \tabularnewline
4 & 5750 & 2600.6409466386 & 5900 \tabularnewline
5 & 4450 & 1634.01346383682 & 3600 \tabularnewline
6 & 3775 & 1519.59424408842 & 3500 \tabularnewline
7 & 3700 & 1564.18242755334 & 3600 \tabularnewline
8 & 3500 & 1388.04418757713 & 3300 \tabularnewline
9 & 3625 & 1800.69431053691 & 4200 \tabularnewline
10 & 3250 & 1613.48484137079 & 3700 \tabularnewline
11 & 4200 & 1061.44555520604 & 2500 \tabularnewline
12 & 3875 & 1297.11217710728 & 2700 \tabularnewline
13 & 4025 & 2028.75166871979 & 4400 \tabularnewline
14 & 4800 & 1503.32963783729 & 2700 \tabularnewline
15 & 4275 & 1450 & 3200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302378&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]4600[/C][C]867.947771086103[/C][C]1600[/C][/ROW]
[ROW][C]2[/C][C]4725[/C][C]950[/C][C]2100[/C][/ROW]
[ROW][C]3[/C][C]5250[/C][C]1470.82743152735[/C][C]3300[/C][/ROW]
[ROW][C]4[/C][C]5750[/C][C]2600.6409466386[/C][C]5900[/C][/ROW]
[ROW][C]5[/C][C]4450[/C][C]1634.01346383682[/C][C]3600[/C][/ROW]
[ROW][C]6[/C][C]3775[/C][C]1519.59424408842[/C][C]3500[/C][/ROW]
[ROW][C]7[/C][C]3700[/C][C]1564.18242755334[/C][C]3600[/C][/ROW]
[ROW][C]8[/C][C]3500[/C][C]1388.04418757713[/C][C]3300[/C][/ROW]
[ROW][C]9[/C][C]3625[/C][C]1800.69431053691[/C][C]4200[/C][/ROW]
[ROW][C]10[/C][C]3250[/C][C]1613.48484137079[/C][C]3700[/C][/ROW]
[ROW][C]11[/C][C]4200[/C][C]1061.44555520604[/C][C]2500[/C][/ROW]
[ROW][C]12[/C][C]3875[/C][C]1297.11217710728[/C][C]2700[/C][/ROW]
[ROW][C]13[/C][C]4025[/C][C]2028.75166871979[/C][C]4400[/C][/ROW]
[ROW][C]14[/C][C]4800[/C][C]1503.32963783729[/C][C]2700[/C][/ROW]
[ROW][C]15[/C][C]4275[/C][C]1450[/C][C]3200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302378&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302378&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	4600	867.947771086103	1600
2	4725	950	2100
3	5250	1470.82743152735	3300
4	5750	2600.6409466386	5900
5	4450	1634.01346383682	3600
6	3775	1519.59424408842	3500
7	3700	1564.18242755334	3600
8	3500	1388.04418757713	3300
9	3625	1800.69431053691	4200
10	3250	1613.48484137079	3700
11	4200	1061.44555520604	2500
12	3875	1297.11217710728	2700
13	4025	2028.75166871979	4400
14	4800	1503.32963783729	2700
15	4275	1450	3200

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	949.104614665448
beta	0.133440430142699
S.D.	0.168643416573312
T-STAT	0.79125786736353
p-value	0.442991240712637

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 949.104614665448 \tabularnewline
beta & 0.133440430142699 \tabularnewline
S.D. & 0.168643416573312 \tabularnewline
T-STAT & 0.79125786736353 \tabularnewline
p-value & 0.442991240712637 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302378&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]949.104614665448[/C][/ROW]
[ROW][C]beta[/C][C]0.133440430142699[/C][/ROW]
[ROW][C]S.D.[/C][C]0.168643416573312[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.79125786736353[/C][/ROW]
[ROW][C]p-value[/C][C]0.442991240712637[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302378&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302378&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	949.104614665448
beta	0.133440430142699
S.D.	0.168643416573312
T-STAT	0.79125786736353
p-value	0.442991240712637

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	6.55649742587432
beta	0.0876934201073659
S.D.	0.489613234480901
T-STAT	0.179107536176673
p-value	0.860614606336904
Lambda	0.912306579892634

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.55649742587432 \tabularnewline
beta & 0.0876934201073659 \tabularnewline
S.D. & 0.489613234480901 \tabularnewline
T-STAT & 0.179107536176673 \tabularnewline
p-value & 0.860614606336904 \tabularnewline
Lambda & 0.912306579892634 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302378&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.55649742587432[/C][/ROW]
[ROW][C]beta[/C][C]0.0876934201073659[/C][/ROW]
[ROW][C]S.D.[/C][C]0.489613234480901[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.179107536176673[/C][/ROW]
[ROW][C]p-value[/C][C]0.860614606336904[/C][/ROW]
[ROW][C]Lambda[/C][C]0.912306579892634[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302378&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302378&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	6.55649742587432
beta	0.0876934201073659
S.D.	0.489613234480901
T-STAT	0.179107536176673
p-value	0.860614606336904
Lambda	0.912306579892634

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 4 ;

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