FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Opgave8: Standard Deviation Mean Plot Gemiddelede Prijs Zakje Frieten - Dav...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 12 May 2008 05:33:25 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/12/t12105920834szz3y49vpjtnxj.htm/, Retrieved Tue, 14 May 2024 21:44:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12332, Retrieved Tue, 14 May 2024 21:44:10 +0000
QR Codes:

Original text written by user:Standard Deviation Mean Plot Gemiddelede Prijs Zakje Frieten
IsPrivate?No (this computation is public)
User-defined keywordsStandard Deviation Mean Plot, Gemiddelede Prijs, Zakje Frieten
Estimated Impact185

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] [Opgave8: Standard...] [2008-05-12 11:33:25] [dffb8b44dc5a91f197edbc7a955d0e55] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.72
1.73
1.73
1.73
1.73
1.73
1.74
1.74
1.74
1.74
1.75
1.75
1.75
1.75
1.75
1.76
1.77
1.77
1.78
1.78
1.78
1.79
1.8
1.8
1.82
1.83
1.85
1.86
1.86
1.87
1.88
1.88
1.89
1.9
1.9
1.9
1.9
1.92
1.92
1.93
1.93
1.93
1.94
1.94
1.95
1.96
1.96
1.96
1.96
1.97
1.97
1.98
1.99
1.99
1.99
2
2
2.01
2.01
2.01
2.02
2.02
2.02
2.02
2.03
2.03
2.03
2.04
2.04
2.05
2.06
2.06

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12332&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12332&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12332&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.735833333333330.009003366373785210.03
21.773333333333330.01825741858350560.05
31.870.02696799449852960.0799999999999998
41.936666666666670.01874873733122190.06
51.990.01705605730844880.0499999999999998
62.0350.01507556722888820.04

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.73583333333333 & 0.00900336637378521 & 0.03 \tabularnewline
2 & 1.77333333333333 & 0.0182574185835056 & 0.05 \tabularnewline
3 & 1.87 & 0.0269679944985296 & 0.0799999999999998 \tabularnewline
4 & 1.93666666666667 & 0.0187487373312219 & 0.06 \tabularnewline
5 & 1.99 & 0.0170560573084488 & 0.0499999999999998 \tabularnewline
6 & 2.035 & 0.0150755672288882 & 0.04 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12332&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]1.73583333333333[/C][C]0.00900336637378521[/C][C]0.03[/C][/ROW]
[ROW][C]2[/C][C]1.77333333333333[/C][C]0.0182574185835056[/C][C]0.05[/C][/ROW]
[ROW][C]3[/C][C]1.87[/C][C]0.0269679944985296[/C][C]0.0799999999999998[/C][/ROW]
[ROW][C]4[/C][C]1.93666666666667[/C][C]0.0187487373312219[/C][C]0.06[/C][/ROW]
[ROW][C]5[/C][C]1.99[/C][C]0.0170560573084488[/C][C]0.0499999999999998[/C][/ROW]
[ROW][C]6[/C][C]2.035[/C][C]0.0150755672288882[/C][C]0.04[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12332&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12332&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
11.735833333333330.009003366373785210.03
21.773333333333330.01825741858350560.05
31.870.02696799449852960.0799999999999998
41.936666666666670.01874873733122190.06
51.990.01705605730844880.0499999999999998
62.0350.01507556722888820.04






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.000975330878814114
beta0.00978421279423298
S.D.0.0239784242122621
T-STAT0.408042359565461
p-value0.704139470630396

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.000975330878814114 \tabularnewline
beta & 0.00978421279423298 \tabularnewline
S.D. & 0.0239784242122621 \tabularnewline
T-STAT & 0.408042359565461 \tabularnewline
p-value & 0.704139470630396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12332&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.000975330878814114[/C][/ROW]
[ROW][C]beta[/C][C]0.00978421279423298[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0239784242122621[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.408042359565461[/C][/ROW]
[ROW][C]p-value[/C][C]0.704139470630396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12332&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12332&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-0.000975330878814114
beta0.00978421279423298
S.D.0.0239784242122621
T-STAT0.408042359565461
p-value0.704139470630396






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.29792556173096
beta1.89468926251335
S.D.2.66483677106708
T-STAT0.710996366863647
p-value0.516348722373014
Lambda-0.894689262513347

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.29792556173096 \tabularnewline
beta & 1.89468926251335 \tabularnewline
S.D. & 2.66483677106708 \tabularnewline
T-STAT & 0.710996366863647 \tabularnewline
p-value & 0.516348722373014 \tabularnewline
Lambda & -0.894689262513347 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12332&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.29792556173096[/C][/ROW]
[ROW][C]beta[/C][C]1.89468926251335[/C][/ROW]
[ROW][C]S.D.[/C][C]2.66483677106708[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.710996366863647[/C][/ROW]
[ROW][C]p-value[/C][C]0.516348722373014[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.894689262513347[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12332&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12332&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-5.29792556173096
beta1.89468926251335
S.D.2.66483677106708
T-STAT0.710996366863647
p-value0.516348722373014
Lambda-0.894689262513347


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')