FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 25 Nov 2009 01:43:01 -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/2009/Nov/25/t1259138785106jwp38ceajtqv.htm/, Retrieved Tue, 07 May 2024 21:55:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59305, Retrieved Tue, 07 May 2024 21:55:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D          [Standard Deviation-Mean Plot] [] [2009-11-25 08:43:01] [ed082d38031561faed979d8cebfeba4d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
285
574
865
1147
1516
1789
2087
2372
2669
2966
3270
3652
329
658
988
1303
1603
1929
2235
2544
2872
3198
3544
3903
332
665
1001
1329
1639
1975
2304
2640
2992
3330
3690
4063
368
738
1103
1474
1846
2224
2608
2984
3351
3736
4122
4558
378
749
1113
1500
1867
2244
2621
2988
3349
3723
4108
4514

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=59305&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=59305&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59305&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
11932.666666666671090.603697152373367
22092.166666666671156.63955517963574
32163.333333333331213.205845783163731
424261363.704780101884190
52429.51348.75063400444136

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1932.66666666667 & 1090.60369715237 & 3367 \tabularnewline
2 & 2092.16666666667 & 1156.6395551796 & 3574 \tabularnewline
3 & 2163.33333333333 & 1213.20584578316 & 3731 \tabularnewline
4 & 2426 & 1363.70478010188 & 4190 \tabularnewline
5 & 2429.5 & 1348.7506340044 & 4136 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59305&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]1932.66666666667[/C][C]1090.60369715237[/C][C]3367[/C][/ROW]
[ROW][C]2[/C][C]2092.16666666667[/C][C]1156.6395551796[/C][C]3574[/C][/ROW]
[ROW][C]3[/C][C]2163.33333333333[/C][C]1213.20584578316[/C][C]3731[/C][/ROW]
[ROW][C]4[/C][C]2426[/C][C]1363.70478010188[/C][C]4190[/C][/ROW]
[ROW][C]5[/C][C]2429.5[/C][C]1348.7506340044[/C][C]4136[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59305&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59305&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
11932.666666666671090.603697152373367
22092.166666666671156.63955517963574
32163.333333333331213.205845783163731
424261363.704780101884190
52429.51348.75063400444136






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha22.4846667048181
beta0.548774366487337
S.D.0.0270071664008052
T-STAT20.3195832670167
p-value0.000260586910978219

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 22.4846667048181 \tabularnewline
beta & 0.548774366487337 \tabularnewline
S.D. & 0.0270071664008052 \tabularnewline
T-STAT & 20.3195832670167 \tabularnewline
p-value & 0.000260586910978219 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59305&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22.4846667048181[/C][/ROW]
[ROW][C]beta[/C][C]0.548774366487337[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0270071664008052[/C][/ROW]
[ROW][C]T-STAT[/C][C]20.3195832670167[/C][/ROW]
[ROW][C]p-value[/C][C]0.000260586910978219[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59305&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59305&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)
alpha22.4846667048181
beta0.548774366487337
S.D.0.0270071664008052
T-STAT20.3195832670167
p-value0.000260586910978219






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.411754275420195
beta0.977937199071747
S.D.0.0490684441059299
T-STAT19.9300633409235
p-value0.000276072104320580
Lambda0.0220628009282526

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.411754275420195 \tabularnewline
beta & 0.977937199071747 \tabularnewline
S.D. & 0.0490684441059299 \tabularnewline
T-STAT & 19.9300633409235 \tabularnewline
p-value & 0.000276072104320580 \tabularnewline
Lambda & 0.0220628009282526 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59305&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.411754275420195[/C][/ROW]
[ROW][C]beta[/C][C]0.977937199071747[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0490684441059299[/C][/ROW]
[ROW][C]T-STAT[/C][C]19.9300633409235[/C][/ROW]
[ROW][C]p-value[/C][C]0.000276072104320580[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0220628009282526[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59305&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59305&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-0.411754275420195
beta0.977937199071747
S.D.0.0490684441059299
T-STAT19.9300633409235
p-value0.000276072104320580
Lambda0.0220628009282526


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')