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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

Tue, 30 Jan 2018 16:05:10 +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/2018/Jan/30/t1517324846t513tjfeeez974k.htm/, Retrieved Thu, 02 May 2024 23:51:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=312901, Retrieved Thu, 02 May 2024 23:51:48 +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] [] [2018-01-30 15:05:10] [2c7049bbcc29bc93573a73f5c62450a0] [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	2 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=312901&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]

2 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=312901&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=312901&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	2 seconds
R Server	Big Analytics Cloud Computing Center

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	67.4416666666667	10.4513990653999	34.6
2	69.5083333333333	7.21292505706166	24.7
3	82.3583333333333	9.67475236547858	30.4
4	79.725	10.3282599960233	31.2
5	80.4583333333333	10.9380452245058	31.1
6	91.3333333333333	19.761364202694	58
7	98.075	10.5339386573287	29.2
8	104.183333333333	12.0536552987302	40.1
9	110.55	15.1121564552275	53
10	88.575	13.8451254960004	43.6
11	99.9916666666667	21.5382306327117	68.1
12	103.366666666667	14.6712045321522	45.9
13	95.5833333333333	14.7945219181925	45.2
14	89.8	12.2452217025848	39
15	87.2833333333333	8.7341371362689	29.4
16	103.633333333333	10.8661554071959	36
17	106.075	18.561060167605	65

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 67.4416666666667 & 10.4513990653999 & 34.6 \tabularnewline
2 & 69.5083333333333 & 7.21292505706166 & 24.7 \tabularnewline
3 & 82.3583333333333 & 9.67475236547858 & 30.4 \tabularnewline
4 & 79.725 & 10.3282599960233 & 31.2 \tabularnewline
5 & 80.4583333333333 & 10.9380452245058 & 31.1 \tabularnewline
6 & 91.3333333333333 & 19.761364202694 & 58 \tabularnewline
7 & 98.075 & 10.5339386573287 & 29.2 \tabularnewline
8 & 104.183333333333 & 12.0536552987302 & 40.1 \tabularnewline
9 & 110.55 & 15.1121564552275 & 53 \tabularnewline
10 & 88.575 & 13.8451254960004 & 43.6 \tabularnewline
11 & 99.9916666666667 & 21.5382306327117 & 68.1 \tabularnewline
12 & 103.366666666667 & 14.6712045321522 & 45.9 \tabularnewline
13 & 95.5833333333333 & 14.7945219181925 & 45.2 \tabularnewline
14 & 89.8 & 12.2452217025848 & 39 \tabularnewline
15 & 87.2833333333333 & 8.7341371362689 & 29.4 \tabularnewline
16 & 103.633333333333 & 10.8661554071959 & 36 \tabularnewline
17 & 106.075 & 18.561060167605 & 65 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=312901&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]67.4416666666667[/C][C]10.4513990653999[/C][C]34.6[/C][/ROW]
[ROW][C]2[/C][C]69.5083333333333[/C][C]7.21292505706166[/C][C]24.7[/C][/ROW]
[ROW][C]3[/C][C]82.3583333333333[/C][C]9.67475236547858[/C][C]30.4[/C][/ROW]
[ROW][C]4[/C][C]79.725[/C][C]10.3282599960233[/C][C]31.2[/C][/ROW]
[ROW][C]5[/C][C]80.4583333333333[/C][C]10.9380452245058[/C][C]31.1[/C][/ROW]
[ROW][C]6[/C][C]91.3333333333333[/C][C]19.761364202694[/C][C]58[/C][/ROW]
[ROW][C]7[/C][C]98.075[/C][C]10.5339386573287[/C][C]29.2[/C][/ROW]
[ROW][C]8[/C][C]104.183333333333[/C][C]12.0536552987302[/C][C]40.1[/C][/ROW]
[ROW][C]9[/C][C]110.55[/C][C]15.1121564552275[/C][C]53[/C][/ROW]
[ROW][C]10[/C][C]88.575[/C][C]13.8451254960004[/C][C]43.6[/C][/ROW]
[ROW][C]11[/C][C]99.9916666666667[/C][C]21.5382306327117[/C][C]68.1[/C][/ROW]
[ROW][C]12[/C][C]103.366666666667[/C][C]14.6712045321522[/C][C]45.9[/C][/ROW]
[ROW][C]13[/C][C]95.5833333333333[/C][C]14.7945219181925[/C][C]45.2[/C][/ROW]
[ROW][C]14[/C][C]89.8[/C][C]12.2452217025848[/C][C]39[/C][/ROW]
[ROW][C]15[/C][C]87.2833333333333[/C][C]8.7341371362689[/C][C]29.4[/C][/ROW]
[ROW][C]16[/C][C]103.633333333333[/C][C]10.8661554071959[/C][C]36[/C][/ROW]
[ROW][C]17[/C][C]106.075[/C][C]18.561060167605[/C][C]65[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=312901&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=312901&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	67.4416666666667	10.4513990653999	34.6
2	69.5083333333333	7.21292505706166	24.7
3	82.3583333333333	9.67475236547858	30.4
4	79.725	10.3282599960233	31.2
5	80.4583333333333	10.9380452245058	31.1
6	91.3333333333333	19.761364202694	58
7	98.075	10.5339386573287	29.2
8	104.183333333333	12.0536552987302	40.1
9	110.55	15.1121564552275	53
10	88.575	13.8451254960004	43.6
11	99.9916666666667	21.5382306327117	68.1
12	103.366666666667	14.6712045321522	45.9
13	95.5833333333333	14.7945219181925	45.2
14	89.8	12.2452217025848	39
15	87.2833333333333	8.7341371362689	29.4
16	103.633333333333	10.8661554071959	36
17	106.075	18.561060167605	65

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-3.09384963980998
beta	0.175820188298833
S.D.	0.0667739445385938
T-STAT	2.63306577908113
p-value	0.0188170574699897

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.09384963980998 \tabularnewline
beta & 0.175820188298833 \tabularnewline
S.D. & 0.0667739445385938 \tabularnewline
T-STAT & 2.63306577908113 \tabularnewline
p-value & 0.0188170574699897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=312901&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.09384963980998[/C][/ROW]
[ROW][C]beta[/C][C]0.175820188298833[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0667739445385938[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.63306577908113[/C][/ROW]
[ROW][C]p-value[/C][C]0.0188170574699897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=312901&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=312901&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	-3.09384963980998
beta	0.175820188298833
S.D.	0.0667739445385938
T-STAT	2.63306577908113
p-value	0.0188170574699897

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.15259119640347
beta	1.25929431618268
S.D.	0.412643030571
T-STAT	3.05177653052837
p-value	0.00807415674514847
Lambda	-0.25929431618268

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.15259119640347 \tabularnewline
beta & 1.25929431618268 \tabularnewline
S.D. & 0.412643030571 \tabularnewline
T-STAT & 3.05177653052837 \tabularnewline
p-value & 0.00807415674514847 \tabularnewline
Lambda & -0.25929431618268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=312901&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.15259119640347[/C][/ROW]
[ROW][C]beta[/C][C]1.25929431618268[/C][/ROW]
[ROW][C]S.D.[/C][C]0.412643030571[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.05177653052837[/C][/ROW]
[ROW][C]p-value[/C][C]0.00807415674514847[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.25929431618268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=312901&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=312901&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	-3.15259119640347
beta	1.25929431618268
S.D.	0.412643030571
T-STAT	3.05177653052837
p-value	0.00807415674514847
Lambda	-0.25929431618268

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code