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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

Mon, 23 Jan 2017 09:40:59 +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/2017/Jan/23/t1485160872d1wbo2sh7wqp4pw.htm/, Retrieved Wed, 15 May 2024 22:16:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=304003, Retrieved Wed, 15 May 2024 22:16:44 +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] [Q7(1)] [2017-01-23 08:40:59] [636d0f72197ac5e1dae4a755427db02a] [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=304003&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=304003&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304003&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	2711.25	227.269846951445	483
2	1728.5	207.19475540338	490
3	2095.25	380.415014600283	916
4	2814.25	212.642697186305	441
5	1687	143.264324472866	325
6	2024	609.433069882712	1441
7	2967	784.231258409576	1880
8	1501.25	147.208185913692	336
9	1961.25	634.202057707163	1467
10	2556.25	369.027889641601	808
11	1540.25	160.483384394356	387
12	1710.75	407.675831186168	947
13	2650	492.948949351418	1168
14	1599.5	211.175282644537	504
15	1738.25	510.425557745691	1134
16	2601.25	384.64388291856	941
17	1503	141.499116605016	339
18	1630.25	265.379445323107	582

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2711.25 & 227.269846951445 & 483 \tabularnewline
2 & 1728.5 & 207.19475540338 & 490 \tabularnewline
3 & 2095.25 & 380.415014600283 & 916 \tabularnewline
4 & 2814.25 & 212.642697186305 & 441 \tabularnewline
5 & 1687 & 143.264324472866 & 325 \tabularnewline
6 & 2024 & 609.433069882712 & 1441 \tabularnewline
7 & 2967 & 784.231258409576 & 1880 \tabularnewline
8 & 1501.25 & 147.208185913692 & 336 \tabularnewline
9 & 1961.25 & 634.202057707163 & 1467 \tabularnewline
10 & 2556.25 & 369.027889641601 & 808 \tabularnewline
11 & 1540.25 & 160.483384394356 & 387 \tabularnewline
12 & 1710.75 & 407.675831186168 & 947 \tabularnewline
13 & 2650 & 492.948949351418 & 1168 \tabularnewline
14 & 1599.5 & 211.175282644537 & 504 \tabularnewline
15 & 1738.25 & 510.425557745691 & 1134 \tabularnewline
16 & 2601.25 & 384.64388291856 & 941 \tabularnewline
17 & 1503 & 141.499116605016 & 339 \tabularnewline
18 & 1630.25 & 265.379445323107 & 582 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304003&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]2711.25[/C][C]227.269846951445[/C][C]483[/C][/ROW]
[ROW][C]2[/C][C]1728.5[/C][C]207.19475540338[/C][C]490[/C][/ROW]
[ROW][C]3[/C][C]2095.25[/C][C]380.415014600283[/C][C]916[/C][/ROW]
[ROW][C]4[/C][C]2814.25[/C][C]212.642697186305[/C][C]441[/C][/ROW]
[ROW][C]5[/C][C]1687[/C][C]143.264324472866[/C][C]325[/C][/ROW]
[ROW][C]6[/C][C]2024[/C][C]609.433069882712[/C][C]1441[/C][/ROW]
[ROW][C]7[/C][C]2967[/C][C]784.231258409576[/C][C]1880[/C][/ROW]
[ROW][C]8[/C][C]1501.25[/C][C]147.208185913692[/C][C]336[/C][/ROW]
[ROW][C]9[/C][C]1961.25[/C][C]634.202057707163[/C][C]1467[/C][/ROW]
[ROW][C]10[/C][C]2556.25[/C][C]369.027889641601[/C][C]808[/C][/ROW]
[ROW][C]11[/C][C]1540.25[/C][C]160.483384394356[/C][C]387[/C][/ROW]
[ROW][C]12[/C][C]1710.75[/C][C]407.675831186168[/C][C]947[/C][/ROW]
[ROW][C]13[/C][C]2650[/C][C]492.948949351418[/C][C]1168[/C][/ROW]
[ROW][C]14[/C][C]1599.5[/C][C]211.175282644537[/C][C]504[/C][/ROW]
[ROW][C]15[/C][C]1738.25[/C][C]510.425557745691[/C][C]1134[/C][/ROW]
[ROW][C]16[/C][C]2601.25[/C][C]384.64388291856[/C][C]941[/C][/ROW]
[ROW][C]17[/C][C]1503[/C][C]141.499116605016[/C][C]339[/C][/ROW]
[ROW][C]18[/C][C]1630.25[/C][C]265.379445323107[/C][C]582[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304003&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304003&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	2711.25	227.269846951445	483
2	1728.5	207.19475540338	490
3	2095.25	380.415014600283	916
4	2814.25	212.642697186305	441
5	1687	143.264324472866	325
6	2024	609.433069882712	1441
7	2967	784.231258409576	1880
8	1501.25	147.208185913692	336
9	1961.25	634.202057707163	1467
10	2556.25	369.027889641601	808
11	1540.25	160.483384394356	387
12	1710.75	407.675831186168	947
13	2650	492.948949351418	1168
14	1599.5	211.175282644537	504
15	1738.25	510.425557745691	1134
16	2601.25	384.64388291856	941
17	1503	141.499116605016	339
18	1630.25	265.379445323107	582

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-2.98474131386135
beta	0.171339124752322
S.D.	0.0836236789014168
T-STAT	2.04893072157602
p-value	0.0572386948649597

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.98474131386135 \tabularnewline
beta & 0.171339124752322 \tabularnewline
S.D. & 0.0836236789014168 \tabularnewline
T-STAT & 2.04893072157602 \tabularnewline
p-value & 0.0572386948649597 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304003&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.98474131386135[/C][/ROW]
[ROW][C]beta[/C][C]0.171339124752322[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0836236789014168[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.04893072157602[/C][/ROW]
[ROW][C]p-value[/C][C]0.0572386948649597[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304003&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304003&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	-2.98474131386135
beta	0.171339124752322
S.D.	0.0836236789014168
T-STAT	2.04893072157602
p-value	0.0572386948649597

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.31640833291584
beta	1.18788708430902
S.D.	0.491735577212762
T-STAT	2.41570294962621
p-value	0.028028705377259
Lambda	-0.187887084309019

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.31640833291584 \tabularnewline
beta & 1.18788708430902 \tabularnewline
S.D. & 0.491735577212762 \tabularnewline
T-STAT & 2.41570294962621 \tabularnewline
p-value & 0.028028705377259 \tabularnewline
Lambda & -0.187887084309019 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304003&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.31640833291584[/C][/ROW]
[ROW][C]beta[/C][C]1.18788708430902[/C][/ROW]
[ROW][C]S.D.[/C][C]0.491735577212762[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.41570294962621[/C][/ROW]
[ROW][C]p-value[/C][C]0.028028705377259[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.187887084309019[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304003&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304003&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	-3.31640833291584
beta	1.18788708430902
S.D.	0.491735577212762
T-STAT	2.41570294962621
p-value	0.028028705377259
Lambda	-0.187887084309019

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code