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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

Thu, 15 Dec 2016 22:07:34 +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/15/t1481836489z2i2nxtnhdoaik8.htm/, Retrieved Fri, 03 May 2024 07:49:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300020, Retrieved Fri, 03 May 2024 07:49:14 +0000

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No (this computation is public)

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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] [variantie N2142] [2016-12-15 21:07:34] [31f526a885cd288e1bc58dc4a6a7fb1f] [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=300020&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=300020&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300020&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	4300.83333333333	790.71588200858	2434
2	4940.16666666667	415.159516622737	1424
3	5471	947.085289429915	2986
4	5847.83333333333	535.114912609404	1774
5	5734.66666666667	266.713783716257	990
6	7005.33333333333	806.18939048671	2670
7	7656.83333333333	398.588836529651	1478
8	7047.5	561.107427730685	1878
9	6642.16666666667	435.014280504013	1860
10	6182.83333333333	383.50484963944	1454

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4300.83333333333 & 790.71588200858 & 2434 \tabularnewline
2 & 4940.16666666667 & 415.159516622737 & 1424 \tabularnewline
3 & 5471 & 947.085289429915 & 2986 \tabularnewline
4 & 5847.83333333333 & 535.114912609404 & 1774 \tabularnewline
5 & 5734.66666666667 & 266.713783716257 & 990 \tabularnewline
6 & 7005.33333333333 & 806.18939048671 & 2670 \tabularnewline
7 & 7656.83333333333 & 398.588836529651 & 1478 \tabularnewline
8 & 7047.5 & 561.107427730685 & 1878 \tabularnewline
9 & 6642.16666666667 & 435.014280504013 & 1860 \tabularnewline
10 & 6182.83333333333 & 383.50484963944 & 1454 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300020&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]4300.83333333333[/C][C]790.71588200858[/C][C]2434[/C][/ROW]
[ROW][C]2[/C][C]4940.16666666667[/C][C]415.159516622737[/C][C]1424[/C][/ROW]
[ROW][C]3[/C][C]5471[/C][C]947.085289429915[/C][C]2986[/C][/ROW]
[ROW][C]4[/C][C]5847.83333333333[/C][C]535.114912609404[/C][C]1774[/C][/ROW]
[ROW][C]5[/C][C]5734.66666666667[/C][C]266.713783716257[/C][C]990[/C][/ROW]
[ROW][C]6[/C][C]7005.33333333333[/C][C]806.18939048671[/C][C]2670[/C][/ROW]
[ROW][C]7[/C][C]7656.83333333333[/C][C]398.588836529651[/C][C]1478[/C][/ROW]
[ROW][C]8[/C][C]7047.5[/C][C]561.107427730685[/C][C]1878[/C][/ROW]
[ROW][C]9[/C][C]6642.16666666667[/C][C]435.014280504013[/C][C]1860[/C][/ROW]
[ROW][C]10[/C][C]6182.83333333333[/C][C]383.50484963944[/C][C]1454[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300020&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300020&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	4300.83333333333	790.71588200858	2434
2	4940.16666666667	415.159516622737	1424
3	5471	947.085289429915	2986
4	5847.83333333333	535.114912609404	1774
5	5734.66666666667	266.713783716257	990
6	7005.33333333333	806.18939048671	2670
7	7656.83333333333	398.588836529651	1478
8	7047.5	561.107427730685	1878
9	6642.16666666667	435.014280504013	1860
10	6182.83333333333	383.50484963944	1454

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	862.648108005724
beta	-0.0507533980811812
S.D.	0.0738077974952777
T-STAT	-0.687642766801548
p-value	0.511118337813689

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 862.648108005724 \tabularnewline
beta & -0.0507533980811812 \tabularnewline
S.D. & 0.0738077974952777 \tabularnewline
T-STAT & -0.687642766801548 \tabularnewline
p-value & 0.511118337813689 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300020&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]862.648108005724[/C][/ROW]
[ROW][C]beta[/C][C]-0.0507533980811812[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0738077974952777[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.687642766801548[/C][/ROW]
[ROW][C]p-value[/C][C]0.511118337813689[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300020&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300020&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	862.648108005724
beta	-0.0507533980811812
S.D.	0.0738077974952777
T-STAT	-0.687642766801548
p-value	0.511118337813689

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	10.3902098452102
beta	-0.476384737226718
S.D.	0.778987924245227
T-STAT	-0.611543160554503
p-value	0.55781418981659
Lambda	1.47638473722672

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 10.3902098452102 \tabularnewline
beta & -0.476384737226718 \tabularnewline
S.D. & 0.778987924245227 \tabularnewline
T-STAT & -0.611543160554503 \tabularnewline
p-value & 0.55781418981659 \tabularnewline
Lambda & 1.47638473722672 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300020&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.3902098452102[/C][/ROW]
[ROW][C]beta[/C][C]-0.476384737226718[/C][/ROW]
[ROW][C]S.D.[/C][C]0.778987924245227[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.611543160554503[/C][/ROW]
[ROW][C]p-value[/C][C]0.55781418981659[/C][/ROW]
[ROW][C]Lambda[/C][C]1.47638473722672[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300020&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300020&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	10.3902098452102
beta	-0.476384737226718
S.D.	0.778987924245227
T-STAT	-0.611543160554503
p-value	0.55781418981659
Lambda	1.47638473722672

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')

Free Statistics

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code