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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 computationThu, 19 May 2011 13:04:18 +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/2011/May/19/t1305810217hdvrx0jgdjbqu3a.htm/, Retrieved Sat, 11 May 2024 18:24:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=122013, Retrieved Sat, 11 May 2024 18:24:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact80

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] [IKO opdracht 8 we...] [2011-05-19 13:04:18] [3f8170910ab21fde7eba151af40022ac] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3893.9
3799.2
3769.6
3768.6
3854.9
3778.5
3779.7
3803.2
3900.3
3792.6
3767.4
3752.6
3829.6
3722.6
3692.9
3681
3762.9
3661.7
3633.1
3621.5
3710
3619.4
3595.2
3573.2
3650.1
3554.2
3537
3528.6
3597.1
3521.9
3516.5
3515.7
3600.2
3517.1
3513.7
3528.2
3608.3
3502.5
3502.5
3495.3
3543.8
3425.3
3418.4
3406.4
3446.1
3341.1
3347
3354.9
3399
3288.9
3279
3275.2
3314
3227.1
3225.3
3228.6
3287.1
3210.1
3213.1
3228
3287
3211
3199.8
3166.3
3164
3156.7
3156
3165.5
3179.2
3182.5
3179.5
3193.5
3219.6
3221.9
3210.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122013&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122013&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122013&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 time2 seconds
R Server'Gwilym Jenkins' @ www.wessa.org






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13805.0416666666750.2230562469857147.7
23675.2583333333373.9110824305842256.4
33548.3583333333344.0396610162276136.4
43449.383.3683393141546267.2
53264.6166666666754.8791868700253188.9
63186.7535.9513686678395131

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3805.04166666667 & 50.2230562469857 & 147.7 \tabularnewline
2 & 3675.25833333333 & 73.9110824305842 & 256.4 \tabularnewline
3 & 3548.35833333333 & 44.0396610162276 & 136.4 \tabularnewline
4 & 3449.3 & 83.3683393141546 & 267.2 \tabularnewline
5 & 3264.61666666667 & 54.8791868700253 & 188.9 \tabularnewline
6 & 3186.75 & 35.9513686678395 & 131 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122013&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]3805.04166666667[/C][C]50.2230562469857[/C][C]147.7[/C][/ROW]
[ROW][C]2[/C][C]3675.25833333333[/C][C]73.9110824305842[/C][C]256.4[/C][/ROW]
[ROW][C]3[/C][C]3548.35833333333[/C][C]44.0396610162276[/C][C]136.4[/C][/ROW]
[ROW][C]4[/C][C]3449.3[/C][C]83.3683393141546[/C][C]267.2[/C][/ROW]
[ROW][C]5[/C][C]3264.61666666667[/C][C]54.8791868700253[/C][C]188.9[/C][/ROW]
[ROW][C]6[/C][C]3186.75[/C][C]35.9513686678395[/C][C]131[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122013&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122013&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
13805.0416666666750.2230562469857147.7
23675.2583333333373.9110824305842256.4
33548.3583333333344.0396610162276136.4
43449.383.3683393141546267.2
53264.6166666666754.8791868700253188.9
63186.7535.9513686678395131






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-17.6928204569265
beta0.0214306776395023
S.D.0.0366703064963992
T-STAT0.584415012773526
p-value0.59031476156538

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -17.6928204569265 \tabularnewline
beta & 0.0214306776395023 \tabularnewline
S.D. & 0.0366703064963992 \tabularnewline
T-STAT & 0.584415012773526 \tabularnewline
p-value & 0.59031476156538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122013&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-17.6928204569265[/C][/ROW]
[ROW][C]beta[/C][C]0.0214306776395023[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0366703064963992[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.584415012773526[/C][/ROW]
[ROW][C]p-value[/C][C]0.59031476156538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122013&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122013&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-17.6928204569265
beta0.0214306776395023
S.D.0.0366703064963992
T-STAT0.584415012773526
p-value0.59031476156538






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.18842586623452
beta1.61748372296376
S.D.2.17014302293071
T-STAT0.745335079703361
p-value0.497482215893659
Lambda-0.617483722963757

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.18842586623452 \tabularnewline
beta & 1.61748372296376 \tabularnewline
S.D. & 2.17014302293071 \tabularnewline
T-STAT & 0.745335079703361 \tabularnewline
p-value & 0.497482215893659 \tabularnewline
Lambda & -0.617483722963757 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122013&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.18842586623452[/C][/ROW]
[ROW][C]beta[/C][C]1.61748372296376[/C][/ROW]
[ROW][C]S.D.[/C][C]2.17014302293071[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.745335079703361[/C][/ROW]
[ROW][C]p-value[/C][C]0.497482215893659[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.617483722963757[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122013&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122013&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-9.18842586623452
beta1.61748372296376
S.D.2.17014302293071
T-STAT0.745335079703361
p-value0.497482215893659
Lambda-0.617483722963757


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')