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Author's title

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, 19 Dec 2017 12:59:42 +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/Dec/19/t1513684801msvbgytt0fsf3ig.htm/, Retrieved Wed, 15 May 2024 22:03:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310312, Retrieved Wed, 15 May 2024 22:03:03 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

100

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

-       [Standard Deviation-Mean Plot] [] [2017-12-19 11:59:42] [0159858f5a3ac6d1271c400c4cf1c45c] [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=310312&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=310312&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310312&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	120.866666666667	16.6158376438283	56.1
2	122.5	15.1789926603124	53.1
3	121.75	15.3055842453305	59.5
4	115.808333333333	15.0983718769056	56.5
5	115.841666666667	13.9013706540257	48.1
6	112.191666666667	13.1667251628927	45.5
7	119.183333333333	16.1365104560115	51.7
8	123.291666666667	15.2870389744404	50.9
9	109.775	16.7058032921606	52.1
10	90.0416666666667	9.80217585616334	35.7
11	100	12.1169303043304	40.8
12	96.875	11.333548349119	42.7
13	87.3666666666667	11.0377314313909	36.5
14	86.2583333333333	10.1756803063466	36.1
15	92.5166666666667	12.465285128441	45.2
16	95.75	11.4551695356686	38.7
17	92.2666666666667	10.5014573303235	33.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 120.866666666667 & 16.6158376438283 & 56.1 \tabularnewline
2 & 122.5 & 15.1789926603124 & 53.1 \tabularnewline
3 & 121.75 & 15.3055842453305 & 59.5 \tabularnewline
4 & 115.808333333333 & 15.0983718769056 & 56.5 \tabularnewline
5 & 115.841666666667 & 13.9013706540257 & 48.1 \tabularnewline
6 & 112.191666666667 & 13.1667251628927 & 45.5 \tabularnewline
7 & 119.183333333333 & 16.1365104560115 & 51.7 \tabularnewline
8 & 123.291666666667 & 15.2870389744404 & 50.9 \tabularnewline
9 & 109.775 & 16.7058032921606 & 52.1 \tabularnewline
10 & 90.0416666666667 & 9.80217585616334 & 35.7 \tabularnewline
11 & 100 & 12.1169303043304 & 40.8 \tabularnewline
12 & 96.875 & 11.333548349119 & 42.7 \tabularnewline
13 & 87.3666666666667 & 11.0377314313909 & 36.5 \tabularnewline
14 & 86.2583333333333 & 10.1756803063466 & 36.1 \tabularnewline
15 & 92.5166666666667 & 12.465285128441 & 45.2 \tabularnewline
16 & 95.75 & 11.4551695356686 & 38.7 \tabularnewline
17 & 92.2666666666667 & 10.5014573303235 & 33.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310312&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]120.866666666667[/C][C]16.6158376438283[/C][C]56.1[/C][/ROW]
[ROW][C]2[/C][C]122.5[/C][C]15.1789926603124[/C][C]53.1[/C][/ROW]
[ROW][C]3[/C][C]121.75[/C][C]15.3055842453305[/C][C]59.5[/C][/ROW]
[ROW][C]4[/C][C]115.808333333333[/C][C]15.0983718769056[/C][C]56.5[/C][/ROW]
[ROW][C]5[/C][C]115.841666666667[/C][C]13.9013706540257[/C][C]48.1[/C][/ROW]
[ROW][C]6[/C][C]112.191666666667[/C][C]13.1667251628927[/C][C]45.5[/C][/ROW]
[ROW][C]7[/C][C]119.183333333333[/C][C]16.1365104560115[/C][C]51.7[/C][/ROW]
[ROW][C]8[/C][C]123.291666666667[/C][C]15.2870389744404[/C][C]50.9[/C][/ROW]
[ROW][C]9[/C][C]109.775[/C][C]16.7058032921606[/C][C]52.1[/C][/ROW]
[ROW][C]10[/C][C]90.0416666666667[/C][C]9.80217585616334[/C][C]35.7[/C][/ROW]
[ROW][C]11[/C][C]100[/C][C]12.1169303043304[/C][C]40.8[/C][/ROW]
[ROW][C]12[/C][C]96.875[/C][C]11.333548349119[/C][C]42.7[/C][/ROW]
[ROW][C]13[/C][C]87.3666666666667[/C][C]11.0377314313909[/C][C]36.5[/C][/ROW]
[ROW][C]14[/C][C]86.2583333333333[/C][C]10.1756803063466[/C][C]36.1[/C][/ROW]
[ROW][C]15[/C][C]92.5166666666667[/C][C]12.465285128441[/C][C]45.2[/C][/ROW]
[ROW][C]16[/C][C]95.75[/C][C]11.4551695356686[/C][C]38.7[/C][/ROW]
[ROW][C]17[/C][C]92.2666666666667[/C][C]10.5014573303235[/C][C]33.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310312&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310312&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	120.866666666667	16.6158376438283	56.1
2	122.5	15.1789926603124	53.1
3	121.75	15.3055842453305	59.5
4	115.808333333333	15.0983718769056	56.5
5	115.841666666667	13.9013706540257	48.1
6	112.191666666667	13.1667251628927	45.5
7	119.183333333333	16.1365104560115	51.7
8	123.291666666667	15.2870389744404	50.9
9	109.775	16.7058032921606	52.1
10	90.0416666666667	9.80217585616334	35.7
11	100	12.1169303043304	40.8
12	96.875	11.333548349119	42.7
13	87.3666666666667	11.0377314313909	36.5
14	86.2583333333333	10.1756803063466	36.1
15	92.5166666666667	12.465285128441	45.2
16	95.75	11.4551695356686	38.7
17	92.2666666666667	10.5014573303235	33.3

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-3.13467951981311
beta	0.155121983249682
S.D.	0.0191564287347974
T-STAT	8.09764624697009
p-value	7.41348194825137e-07

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.13467951981311 \tabularnewline
beta & 0.155121983249682 \tabularnewline
S.D. & 0.0191564287347974 \tabularnewline
T-STAT & 8.09764624697009 \tabularnewline
p-value & 7.41348194825137e-07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310312&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.13467951981311[/C][/ROW]
[ROW][C]beta[/C][C]0.155121983249682[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0191564287347974[/C][/ROW]
[ROW][C]T-STAT[/C][C]8.09764624697009[/C][/ROW]
[ROW][C]p-value[/C][C]7.41348194825137e-07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310312&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310312&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	-3.13467951981311
beta	0.155121983249682
S.D.	0.0191564287347974
T-STAT	8.09764624697009
p-value	7.41348194825137e-07

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.26059721533791
beta	1.25312466863094
S.D.	0.144970620703521
T-STAT	8.64399050338412
p-value	3.27682444928182e-07
Lambda	-0.253124668630936

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.26059721533791 \tabularnewline
beta & 1.25312466863094 \tabularnewline
S.D. & 0.144970620703521 \tabularnewline
T-STAT & 8.64399050338412 \tabularnewline
p-value & 3.27682444928182e-07 \tabularnewline
Lambda & -0.253124668630936 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310312&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.26059721533791[/C][/ROW]
[ROW][C]beta[/C][C]1.25312466863094[/C][/ROW]
[ROW][C]S.D.[/C][C]0.144970620703521[/C][/ROW]
[ROW][C]T-STAT[/C][C]8.64399050338412[/C][/ROW]
[ROW][C]p-value[/C][C]3.27682444928182e-07[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.253124668630936[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310312&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310312&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	-3.26059721533791
beta	1.25312466863094
S.D.	0.144970620703521
T-STAT	8.64399050338412
p-value	3.27682444928182e-07
Lambda	-0.253124668630936

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code