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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

Fri, 09 Dec 2016 09:23:05 +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/09/t1481271794wz2kokn72qlfi21.htm/, Retrieved Fri, 01 Nov 2024 03:39:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298441, Retrieved Fri, 01 Nov 2024 03:39:46 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

146

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

-       [Standard Deviation-Mean Plot] [] [2016-12-09 08:23:05] [94ac3c9a028ddd47e8862e80eac9f626] [Current]

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Histogram

Boxplots

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=298441&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=298441&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298441&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	3920.83333333333	290.343318201474	950
2	4379.16666666667	271.743807601382	800
3	4650	222.588082667187	700
4	4845.83333333333	293.457704350089	950
5	5012.5	365.640782487651	1200
6	5425	355.796162276814	1150
7	5725	304.138126514911	1100
8	5816.66666666667	312.855857990206	1050
9	5687.5	429.12437273211	1400

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3920.83333333333 & 290.343318201474 & 950 \tabularnewline
2 & 4379.16666666667 & 271.743807601382 & 800 \tabularnewline
3 & 4650 & 222.588082667187 & 700 \tabularnewline
4 & 4845.83333333333 & 293.457704350089 & 950 \tabularnewline
5 & 5012.5 & 365.640782487651 & 1200 \tabularnewline
6 & 5425 & 355.796162276814 & 1150 \tabularnewline
7 & 5725 & 304.138126514911 & 1100 \tabularnewline
8 & 5816.66666666667 & 312.855857990206 & 1050 \tabularnewline
9 & 5687.5 & 429.12437273211 & 1400 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298441&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]3920.83333333333[/C][C]290.343318201474[/C][C]950[/C][/ROW]
[ROW][C]2[/C][C]4379.16666666667[/C][C]271.743807601382[/C][C]800[/C][/ROW]
[ROW][C]3[/C][C]4650[/C][C]222.588082667187[/C][C]700[/C][/ROW]
[ROW][C]4[/C][C]4845.83333333333[/C][C]293.457704350089[/C][C]950[/C][/ROW]
[ROW][C]5[/C][C]5012.5[/C][C]365.640782487651[/C][C]1200[/C][/ROW]
[ROW][C]6[/C][C]5425[/C][C]355.796162276814[/C][C]1150[/C][/ROW]
[ROW][C]7[/C][C]5725[/C][C]304.138126514911[/C][C]1100[/C][/ROW]
[ROW][C]8[/C][C]5816.66666666667[/C][C]312.855857990206[/C][C]1050[/C][/ROW]
[ROW][C]9[/C][C]5687.5[/C][C]429.12437273211[/C][C]1400[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298441&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298441&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	3920.83333333333	290.343318201474	950
2	4379.16666666667	271.743807601382	800
3	4650	222.588082667187	700
4	4845.83333333333	293.457704350089	950
5	5012.5	365.640782487651	1200
6	5425	355.796162276814	1150
7	5725	304.138126514911	1100
8	5816.66666666667	312.855857990206	1050
9	5687.5	429.12437273211	1400

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	64.3955834064385
beta	0.0498460921454799
S.D.	0.0285699499568434
T-STAT	1.74470351613409
p-value	0.124551629422609

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 64.3955834064385 \tabularnewline
beta & 0.0498460921454799 \tabularnewline
S.D. & 0.0285699499568434 \tabularnewline
T-STAT & 1.74470351613409 \tabularnewline
p-value & 0.124551629422609 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298441&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]64.3955834064385[/C][/ROW]
[ROW][C]beta[/C][C]0.0498460921454799[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0285699499568434[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.74470351613409[/C][/ROW]
[ROW][C]p-value[/C][C]0.124551629422609[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298441&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298441&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	64.3955834064385
beta	0.0498460921454799
S.D.	0.0285699499568434
T-STAT	1.74470351613409
p-value	0.124551629422609

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-0.700261623021304
beta	0.756002766093444
S.D.	0.442969535410523
T-STAT	1.70666988508096
p-value	0.131645930594538
Lambda	0.243997233906556

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.700261623021304 \tabularnewline
beta & 0.756002766093444 \tabularnewline
S.D. & 0.442969535410523 \tabularnewline
T-STAT & 1.70666988508096 \tabularnewline
p-value & 0.131645930594538 \tabularnewline
Lambda & 0.243997233906556 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298441&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.700261623021304[/C][/ROW]
[ROW][C]beta[/C][C]0.756002766093444[/C][/ROW]
[ROW][C]S.D.[/C][C]0.442969535410523[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.70666988508096[/C][/ROW]
[ROW][C]p-value[/C][C]0.131645930594538[/C][/ROW]
[ROW][C]Lambda[/C][C]0.243997233906556[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298441&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298441&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	-0.700261623021304
beta	0.756002766093444
S.D.	0.442969535410523
T-STAT	1.70666988508096
p-value	0.131645930594538
Lambda	0.243997233906556

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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code