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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 09 Dec 2008 16:46:58 -0700
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/Dec/10/t1228866611frfyaf73jpivk8v.htm/, Retrieved Sun, 26 May 2024 04:11:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31850, Retrieved Sun, 26 May 2024 04:11:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact209

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Standard Deviation-Mean Plot] [Step 1 eigen tijd...] [2008-12-09 23:46:58] [9f72e095d5529918bf5b0810c01bf6ce] [Current]
Feedback Forum
2008-12-16 18:04:24 [Julian De Ruyter] [reply] 
Juiste berekening en conlcusie

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,1372
1,1139
1,1222
1,1692
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
1,4227
1,4684
1,457
1,4718
1,4748
1,5527
1,575
1,5557
1,5553
1,577

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=31850&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=31850&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31850&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
11.19220.05058289326352430.1507
21.272333333333330.0445873062517560.1243
31.216616666666670.03001944319431940.0983999999999998
41.305733333333330.03231226430076390.0904999999999998
51.47140.07547669116416610.2128

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.1922 & 0.0505828932635243 & 0.1507 \tabularnewline
2 & 1.27233333333333 & 0.044587306251756 & 0.1243 \tabularnewline
3 & 1.21661666666667 & 0.0300194431943194 & 0.0983999999999998 \tabularnewline
4 & 1.30573333333333 & 0.0323122643007639 & 0.0904999999999998 \tabularnewline
5 & 1.4714 & 0.0754766911641661 & 0.2128 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31850&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]1.1922[/C][C]0.0505828932635243[/C][C]0.1507[/C][/ROW]
[ROW][C]2[/C][C]1.27233333333333[/C][C]0.044587306251756[/C][C]0.1243[/C][/ROW]
[ROW][C]3[/C][C]1.21661666666667[/C][C]0.0300194431943194[/C][C]0.0983999999999998[/C][/ROW]
[ROW][C]4[/C][C]1.30573333333333[/C][C]0.0323122643007639[/C][C]0.0904999999999998[/C][/ROW]
[ROW][C]5[/C][C]1.4714[/C][C]0.0754766911641661[/C][C]0.2128[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31850&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31850&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
11.19220.05058289326352430.1507
21.272333333333330.0445873062517560.1243
31.216616666666670.03001944319431940.0983999999999998
41.305733333333330.03231226430076390.0904999999999998
51.47140.07547669116416610.2128






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.110218266856095
beta0.121405316550322
S.D.0.0653134752286382
T-STAT1.85880962734455
p-value0.160018823406334

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.110218266856095 \tabularnewline
beta & 0.121405316550322 \tabularnewline
S.D. & 0.0653134752286382 \tabularnewline
T-STAT & 1.85880962734455 \tabularnewline
p-value & 0.160018823406334 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31850&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.110218266856095[/C][/ROW]
[ROW][C]beta[/C][C]0.121405316550322[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0653134752286382[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.85880962734455[/C][/ROW]
[ROW][C]p-value[/C][C]0.160018823406334[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31850&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31850&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-0.110218266856095
beta0.121405316550322
S.D.0.0653134752286382
T-STAT1.85880962734455
p-value0.160018823406334






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.85145508699257
beta2.87640130961720
S.D.1.99753808947305
T-STAT1.43997319739520
p-value0.245497014371922
Lambda-1.87640130961720

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.85145508699257 \tabularnewline
beta & 2.87640130961720 \tabularnewline
S.D. & 1.99753808947305 \tabularnewline
T-STAT & 1.43997319739520 \tabularnewline
p-value & 0.245497014371922 \tabularnewline
Lambda & -1.87640130961720 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31850&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.85145508699257[/C][/ROW]
[ROW][C]beta[/C][C]2.87640130961720[/C][/ROW]
[ROW][C]S.D.[/C][C]1.99753808947305[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.43997319739520[/C][/ROW]
[ROW][C]p-value[/C][C]0.245497014371922[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.87640130961720[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31850&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31850&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-3.85145508699257
beta2.87640130961720
S.D.1.99753808947305
T-STAT1.43997319739520
p-value0.245497014371922
Lambda-1.87640130961720


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')