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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

Fri, 25 Dec 2015 09:50:15 +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/2015/Dec/25/t1451037198je7wr8jiz5itijz.htm/, Retrieved Thu, 31 Oct 2024 23:58:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=287079, Retrieved Thu, 31 Oct 2024 23:58:12 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

180

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

-       [Standard Deviation-Mean Plot] [] [2015-12-25 09:50:15] [e7bd1b63287b3004f428c98394187272] [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	'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287079&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287079&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287079&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	'George Udny Yule' @ yule.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	64401.05	2607.88961486742	5683.7
2	66322.85	2356.78091825835	4810.8
3	68641.275	2743.60926685391	5935.7
4	70564.025	2946.80229556831	6292.89999999999
5	74589.175	3122.76991614282	6991
6	77787.5	3550.67291932107	7786.2
7	81842.1	3653.28765269495	8046.10000000001
8	86267.15	3494.97653449442	7435.7
9	88766.325	2600.75198916903	4970.5
10	87425.725	3739.07326430405	8324.60000000001
11	91436.7	4444.30106615952	10170.3
12	94978.825	3901.31247007551	8267.2
13	97042.825	3941.72005802458	8624.39999999999
14	98810.35	4240.08514183383	9046.2
15	100506.8	3964.53621079019	8399.79999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 64401.05 & 2607.88961486742 & 5683.7 \tabularnewline
2 & 66322.85 & 2356.78091825835 & 4810.8 \tabularnewline
3 & 68641.275 & 2743.60926685391 & 5935.7 \tabularnewline
4 & 70564.025 & 2946.80229556831 & 6292.89999999999 \tabularnewline
5 & 74589.175 & 3122.76991614282 & 6991 \tabularnewline
6 & 77787.5 & 3550.67291932107 & 7786.2 \tabularnewline
7 & 81842.1 & 3653.28765269495 & 8046.10000000001 \tabularnewline
8 & 86267.15 & 3494.97653449442 & 7435.7 \tabularnewline
9 & 88766.325 & 2600.75198916903 & 4970.5 \tabularnewline
10 & 87425.725 & 3739.07326430405 & 8324.60000000001 \tabularnewline
11 & 91436.7 & 4444.30106615952 & 10170.3 \tabularnewline
12 & 94978.825 & 3901.31247007551 & 8267.2 \tabularnewline
13 & 97042.825 & 3941.72005802458 & 8624.39999999999 \tabularnewline
14 & 98810.35 & 4240.08514183383 & 9046.2 \tabularnewline
15 & 100506.8 & 3964.53621079019 & 8399.79999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287079&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]64401.05[/C][C]2607.88961486742[/C][C]5683.7[/C][/ROW]
[ROW][C]2[/C][C]66322.85[/C][C]2356.78091825835[/C][C]4810.8[/C][/ROW]
[ROW][C]3[/C][C]68641.275[/C][C]2743.60926685391[/C][C]5935.7[/C][/ROW]
[ROW][C]4[/C][C]70564.025[/C][C]2946.80229556831[/C][C]6292.89999999999[/C][/ROW]
[ROW][C]5[/C][C]74589.175[/C][C]3122.76991614282[/C][C]6991[/C][/ROW]
[ROW][C]6[/C][C]77787.5[/C][C]3550.67291932107[/C][C]7786.2[/C][/ROW]
[ROW][C]7[/C][C]81842.1[/C][C]3653.28765269495[/C][C]8046.10000000001[/C][/ROW]
[ROW][C]8[/C][C]86267.15[/C][C]3494.97653449442[/C][C]7435.7[/C][/ROW]
[ROW][C]9[/C][C]88766.325[/C][C]2600.75198916903[/C][C]4970.5[/C][/ROW]
[ROW][C]10[/C][C]87425.725[/C][C]3739.07326430405[/C][C]8324.60000000001[/C][/ROW]
[ROW][C]11[/C][C]91436.7[/C][C]4444.30106615952[/C][C]10170.3[/C][/ROW]
[ROW][C]12[/C][C]94978.825[/C][C]3901.31247007551[/C][C]8267.2[/C][/ROW]
[ROW][C]13[/C][C]97042.825[/C][C]3941.72005802458[/C][C]8624.39999999999[/C][/ROW]
[ROW][C]14[/C][C]98810.35[/C][C]4240.08514183383[/C][C]9046.2[/C][/ROW]
[ROW][C]15[/C][C]100506.8[/C][C]3964.53621079019[/C][C]8399.79999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287079&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287079&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	64401.05	2607.88961486742	5683.7
2	66322.85	2356.78091825835	4810.8
3	68641.275	2743.60926685391	5935.7
4	70564.025	2946.80229556831	6292.89999999999
5	74589.175	3122.76991614282	6991
6	77787.5	3550.67291932107	7786.2
7	81842.1	3653.28765269495	8046.10000000001
8	86267.15	3494.97653449442	7435.7
9	88766.325	2600.75198916903	4970.5
10	87425.725	3739.07326430405	8324.60000000001
11	91436.7	4444.30106615952	10170.3
12	94978.825	3901.31247007551	8267.2
13	97042.825	3941.72005802458	8624.39999999999
14	98810.35	4240.08514183383	9046.2
15	100506.8	3964.53621079019	8399.79999999999

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-169.383351475298
beta	0.0431007414047001
S.D.	0.00853695101260972
T-STAT	5.0487277414427
p-value	0.000222947791597821

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -169.383351475298 \tabularnewline
beta & 0.0431007414047001 \tabularnewline
S.D. & 0.00853695101260972 \tabularnewline
T-STAT & 5.0487277414427 \tabularnewline
p-value & 0.000222947791597821 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287079&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-169.383351475298[/C][/ROW]
[ROW][C]beta[/C][C]0.0431007414047001[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00853695101260972[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.0487277414427[/C][/ROW]
[ROW][C]p-value[/C][C]0.000222947791597821[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287079&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287079&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	-169.383351475298
beta	0.0431007414047001
S.D.	0.00853695101260972
T-STAT	5.0487277414427
p-value	0.000222947791597821

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.94527425215613
beta	1.06584996094208
S.D.	0.211690867224403
T-STAT	5.03493596543408
p-value	0.000228429616624577
Lambda	-0.0658499609420764

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.94527425215613 \tabularnewline
beta & 1.06584996094208 \tabularnewline
S.D. & 0.211690867224403 \tabularnewline
T-STAT & 5.03493596543408 \tabularnewline
p-value & 0.000228429616624577 \tabularnewline
Lambda & -0.0658499609420764 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287079&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.94527425215613[/C][/ROW]
[ROW][C]beta[/C][C]1.06584996094208[/C][/ROW]
[ROW][C]S.D.[/C][C]0.211690867224403[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.03493596543408[/C][/ROW]
[ROW][C]p-value[/C][C]0.000228429616624577[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0658499609420764[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287079&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287079&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	-3.94527425215613
beta	1.06584996094208
S.D.	0.211690867224403
T-STAT	5.03493596543408
p-value	0.000228429616624577
Lambda	-0.0658499609420764

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

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')

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Dataset

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Figures (Output of Computation)

Input Parameters & R Code