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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, 20 Dec 2016 00:56:00 +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/20/t1482192151zl57whe13a604kd.htm/, Retrieved Sun, 28 Apr 2024 10:20:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301548, Retrieved Sun, 28 Apr 2024 10:20:44 +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] [Standard Deviatio...] [2016-12-19 23:56:00] [9b0b4f5f4290a2ed9efd388f9ce31ae7] [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=301548&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=301548&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301548&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	2328.33333333333	564.707862258858	2056
2	2837.33333333333	621.539340279561	1804
3	3436.66666666667	899.1532717288	3191
4	2819.25	730.127401709642	2389
5	2980.66666666667	1069.72420688132	3601
6	3429.25	888.061435733116	3669
7	3632.75	698.78259397066	2020
8	2982.83333333333	599.140571354022	1904
9	2817.83333333333	696.648839847312	2388
10	2425.25	502.065393241666	1572

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2328.33333333333 & 564.707862258858 & 2056 \tabularnewline
2 & 2837.33333333333 & 621.539340279561 & 1804 \tabularnewline
3 & 3436.66666666667 & 899.1532717288 & 3191 \tabularnewline
4 & 2819.25 & 730.127401709642 & 2389 \tabularnewline
5 & 2980.66666666667 & 1069.72420688132 & 3601 \tabularnewline
6 & 3429.25 & 888.061435733116 & 3669 \tabularnewline
7 & 3632.75 & 698.78259397066 & 2020 \tabularnewline
8 & 2982.83333333333 & 599.140571354022 & 1904 \tabularnewline
9 & 2817.83333333333 & 696.648839847312 & 2388 \tabularnewline
10 & 2425.25 & 502.065393241666 & 1572 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301548&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]2328.33333333333[/C][C]564.707862258858[/C][C]2056[/C][/ROW]
[ROW][C]2[/C][C]2837.33333333333[/C][C]621.539340279561[/C][C]1804[/C][/ROW]
[ROW][C]3[/C][C]3436.66666666667[/C][C]899.1532717288[/C][C]3191[/C][/ROW]
[ROW][C]4[/C][C]2819.25[/C][C]730.127401709642[/C][C]2389[/C][/ROW]
[ROW][C]5[/C][C]2980.66666666667[/C][C]1069.72420688132[/C][C]3601[/C][/ROW]
[ROW][C]6[/C][C]3429.25[/C][C]888.061435733116[/C][C]3669[/C][/ROW]
[ROW][C]7[/C][C]3632.75[/C][C]698.78259397066[/C][C]2020[/C][/ROW]
[ROW][C]8[/C][C]2982.83333333333[/C][C]599.140571354022[/C][C]1904[/C][/ROW]
[ROW][C]9[/C][C]2817.83333333333[/C][C]696.648839847312[/C][C]2388[/C][/ROW]
[ROW][C]10[/C][C]2425.25[/C][C]502.065393241666[/C][C]1572[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301548&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301548&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	2328.33333333333	564.707862258858	2056
2	2837.33333333333	621.539340279561	1804
3	3436.66666666667	899.1532717288	3191
4	2819.25	730.127401709642	2389
5	2980.66666666667	1069.72420688132	3601
6	3429.25	888.061435733116	3669
7	3632.75	698.78259397066	2020
8	2982.83333333333	599.140571354022	1904
9	2817.83333333333	696.648839847312	2388
10	2425.25	502.065393241666	1572

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	34.7257625823251
beta	0.233164514329044
S.D.	0.120334028011058
T-STAT	1.93764405781893
p-value	0.088668258718928

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 34.7257625823251 \tabularnewline
beta & 0.233164514329044 \tabularnewline
S.D. & 0.120334028011058 \tabularnewline
T-STAT & 1.93764405781893 \tabularnewline
p-value & 0.088668258718928 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301548&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]34.7257625823251[/C][/ROW]
[ROW][C]beta[/C][C]0.233164514329044[/C][/ROW]
[ROW][C]S.D.[/C][C]0.120334028011058[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.93764405781893[/C][/ROW]
[ROW][C]p-value[/C][C]0.088668258718928[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301548&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301548&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	34.7257625823251
beta	0.233164514329044
S.D.	0.120334028011058
T-STAT	1.93764405781893
p-value	0.088668258718928

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.67962630290288
beta	1.03215005879179
S.D.	0.439172099248051
T-STAT	2.35021774051455
p-value	0.0466653931189485
Lambda	-0.0321500587917851

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.67962630290288 \tabularnewline
beta & 1.03215005879179 \tabularnewline
S.D. & 0.439172099248051 \tabularnewline
T-STAT & 2.35021774051455 \tabularnewline
p-value & 0.0466653931189485 \tabularnewline
Lambda & -0.0321500587917851 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301548&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.67962630290288[/C][/ROW]
[ROW][C]beta[/C][C]1.03215005879179[/C][/ROW]
[ROW][C]S.D.[/C][C]0.439172099248051[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.35021774051455[/C][/ROW]
[ROW][C]p-value[/C][C]0.0466653931189485[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0321500587917851[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301548&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301548&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	-1.67962630290288
beta	1.03215005879179
S.D.	0.439172099248051
T-STAT	2.35021774051455
p-value	0.0466653931189485
Lambda	-0.0321500587917851

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