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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 10 Mar 2015 11:23:29 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Mar/10/t1425986641hp6q8z13naiumr0.htm/, Retrieved Fri, 17 May 2024 10:59:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278116, Retrieved Fri, 17 May 2024 10:59:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [standard deviatio...] [2015-03-10 11:23:29] [cab9dc260884be88f444bea8f40c034b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3862.5
3875.7
3875.9
3877.7
3880.4
3883.4
3884.2
3884.8
3894.9
3903.3
3911.2
3928.9
3945.6
3965.7
3992.3
4008.7
4014.8
4020.6
4037.5
4058.5
4082.3
4102.4
4127.1
4144.4
4161
4168.2
4178.3
4174.1
4165.7
4167.9
4158.3
4158.3
4143.7
4157.5
4164.8
4173.9
4181.2
4190.7
4206.6
4222.1
4245.8
4255.4
4266.1
4273.6
4282.1
4299.8
4315.7
4331.7
4348.4
4367.8
4387.2
4410.9
4436
4453.8
4469.1
4472
4458.2
4449
4441.5
4445.7
4453.9
4469.7
4487.5
4504
4524.1
4540.5
4548.4
4554.2
4558
4557.5
4554.5
4550
4543.8
4538.2
4543.3
4545.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278116&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278116&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278116&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13888.57518.206947974480966.4000000000001
24041.6583333333362.655297364858198.8
34164.308333333339.3811666587257834.6000000000004
44255.948.4852179910162150.5
54428.340.5861597547288123.6
64525.1916666666737.2239770805992104.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3888.575 & 18.2069479744809 & 66.4000000000001 \tabularnewline
2 & 4041.65833333333 & 62.655297364858 & 198.8 \tabularnewline
3 & 4164.30833333333 & 9.38116665872578 & 34.6000000000004 \tabularnewline
4 & 4255.9 & 48.4852179910162 & 150.5 \tabularnewline
5 & 4428.3 & 40.5861597547288 & 123.6 \tabularnewline
6 & 4525.19166666667 & 37.2239770805992 & 104.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278116&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]3888.575[/C][C]18.2069479744809[/C][C]66.4000000000001[/C][/ROW]
[ROW][C]2[/C][C]4041.65833333333[/C][C]62.655297364858[/C][C]198.8[/C][/ROW]
[ROW][C]3[/C][C]4164.30833333333[/C][C]9.38116665872578[/C][C]34.6000000000004[/C][/ROW]
[ROW][C]4[/C][C]4255.9[/C][C]48.4852179910162[/C][C]150.5[/C][/ROW]
[ROW][C]5[/C][C]4428.3[/C][C]40.5861597547288[/C][C]123.6[/C][/ROW]
[ROW][C]6[/C][C]4525.19166666667[/C][C]37.2239770805992[/C][C]104.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278116&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278116&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13888.57518.206947974480966.4000000000001
24041.6583333333362.655297364858198.8
34164.308333333339.3811666587257834.6000000000004
44255.948.4852179910162150.5
54428.340.5861597547288123.6
64525.1916666666737.2239770805992104.1






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-29.6534568606119
beta0.0155888613359747
S.D.0.0404093296623892
T-STAT0.385773816745194
p-value0.719303166224995

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -29.6534568606119 \tabularnewline
beta & 0.0155888613359747 \tabularnewline
S.D. & 0.0404093296623892 \tabularnewline
T-STAT & 0.385773816745194 \tabularnewline
p-value & 0.719303166224995 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278116&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-29.6534568606119[/C][/ROW]
[ROW][C]beta[/C][C]0.0155888613359747[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0404093296623892[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.385773816745194[/C][/ROW]
[ROW][C]p-value[/C][C]0.719303166224995[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278116&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278116&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-29.6534568606119
beta0.0155888613359747
S.D.0.0404093296623892
T-STAT0.385773816745194
p-value0.719303166224995






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-27.054512770454
beta3.65075171777131
S.D.5.99617512654735
T-STAT0.608846746588177
p-value0.5755083976099
Lambda-2.65075171777131

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -27.054512770454 \tabularnewline
beta & 3.65075171777131 \tabularnewline
S.D. & 5.99617512654735 \tabularnewline
T-STAT & 0.608846746588177 \tabularnewline
p-value & 0.5755083976099 \tabularnewline
Lambda & -2.65075171777131 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278116&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-27.054512770454[/C][/ROW]
[ROW][C]beta[/C][C]3.65075171777131[/C][/ROW]
[ROW][C]S.D.[/C][C]5.99617512654735[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.608846746588177[/C][/ROW]
[ROW][C]p-value[/C][C]0.5755083976099[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.65075171777131[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278116&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278116&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-27.054512770454
beta3.65075171777131
S.D.5.99617512654735
T-STAT0.608846746588177
p-value0.5755083976099
Lambda-2.65075171777131


Figures (Output of Computation)

Input Parameters & R Code

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')