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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 computationWed, 21 Nov 2007 12:22:54 -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/2007/Nov/21/t1195672783gilnzax6y8eyg11.htm/, Retrieved Tue, 07 May 2024 14:43:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5870, Retrieved Tue, 07 May 2024 14:43:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact257

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] [Ws9SMPEa] [2007-11-21 19:22:54] [142ab5472309a9ae9a3b52678758dc4a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1178
2141
2238
2685
4341
5376
4478
6404
4617
3024
1897
2075
1351
2211
2453
3042
4765
4992
4601
6266
4812
3159
1916
2237
1595
2453
2226
3597
4706
4974
5756
5493
5004
3225
2006
2291
1588
2105
2191
3591
4668
4885
5822
5599
5340
3082
2010
2301
1514
1979
2480
3499
4676
5585
5610
5796
6199
3030
1930
2552

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5870&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5870&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5870&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13371.166666666671623.327493611555226
23483.751543.715183633894287
33610.51505.482435512413565
43598.51581.284374401793137
53737.51730.585423806321858

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3371.16666666667 & 1623.32749361155 & 5226 \tabularnewline
2 & 3483.75 & 1543.71518363389 & 4287 \tabularnewline
3 & 3610.5 & 1505.48243551241 & 3565 \tabularnewline
4 & 3598.5 & 1581.28437440179 & 3137 \tabularnewline
5 & 3737.5 & 1730.58542380632 & 1858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5870&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]3371.16666666667[/C][C]1623.32749361155[/C][C]5226[/C][/ROW]
[ROW][C]2[/C][C]3483.75[/C][C]1543.71518363389[/C][C]4287[/C][/ROW]
[ROW][C]3[/C][C]3610.5[/C][C]1505.48243551241[/C][C]3565[/C][/ROW]
[ROW][C]4[/C][C]3598.5[/C][C]1581.28437440179[/C][C]3137[/C][/ROW]
[ROW][C]5[/C][C]3737.5[/C][C]1730.58542380632[/C][C]1858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5870&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5870&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
13371.166666666671623.327493611555226
23483.751543.715183633894287
33610.51505.482435512413565
43598.51581.284374401793137
53737.51730.585423806321858






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha784.303405443232
beta0.228233401859391
S.D.0.335392852107078
T-STAT0.680495724418494
p-value0.545004027089159

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 784.303405443232 \tabularnewline
beta & 0.228233401859391 \tabularnewline
S.D. & 0.335392852107078 \tabularnewline
T-STAT & 0.680495724418494 \tabularnewline
p-value & 0.545004027089159 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5870&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]784.303405443232[/C][/ROW]
[ROW][C]beta[/C][C]0.228233401859391[/C][/ROW]
[ROW][C]S.D.[/C][C]0.335392852107078[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.680495724418494[/C][/ROW]
[ROW][C]p-value[/C][C]0.545004027089159[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5870&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5870&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)
alpha784.303405443232
beta0.228233401859391
S.D.0.335392852107078
T-STAT0.680495724418494
p-value0.545004027089159






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.61794105175088
beta0.459424880346803
S.D.0.743694539671388
T-STAT0.617760190292384
p-value0.580459599418732
Lambda0.540575119653196

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.61794105175088 \tabularnewline
beta & 0.459424880346803 \tabularnewline
S.D. & 0.743694539671388 \tabularnewline
T-STAT & 0.617760190292384 \tabularnewline
p-value & 0.580459599418732 \tabularnewline
Lambda & 0.540575119653196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5870&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.61794105175088[/C][/ROW]
[ROW][C]beta[/C][C]0.459424880346803[/C][/ROW]
[ROW][C]S.D.[/C][C]0.743694539671388[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.617760190292384[/C][/ROW]
[ROW][C]p-value[/C][C]0.580459599418732[/C][/ROW]
[ROW][C]Lambda[/C][C]0.540575119653196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5870&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5870&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)
alpha3.61794105175088
beta0.459424880346803
S.D.0.743694539671388
T-STAT0.617760190292384
p-value0.580459599418732
Lambda0.540575119653196


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')