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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 computationMon, 06 Dec 2010 17:23:48 +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/2010/Dec/06/t1291656152737z56xh9i387z9.htm/, Retrieved Mon, 29 Apr 2024 06:55:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105717, Retrieved Mon, 29 Apr 2024 06:55:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact157

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] [Het aantal werklo...] [2010-12-06 17:23:48] [6b57770a9d87785617c80b642e34c9c4] [Current]
- RMP     [Classical Decomposition] [Het aantal werklo...] [2010-12-14 22:42:47] [3e532679ec753acf7892d78d91c458c8]
- RMP       [Exponential Smoothing] [Het aantal werklo...] [2011-01-16 20:21:55] [74be16979710d4c4e7c6647856088456]
- R PD      [Classical Decomposition] [standard deviatio...] [2011-05-19 08:08:59] [d460d5fbfa759ad1669bb34c73f51f31]
-   P     [Standard Deviation-Mean Plot] [Het aantal werklo...] [2011-01-16 15:35:13] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
591000
589000
584000
573000
567000
569000
621000
629000
628000
612000
595000
597000
593000
590000
580000
574000
573000
573000
620000
626000
620000
588000
566000
557000
561000
549000
532000
526000
511000
499000
555000
565000
542000
527000
510000
514000
517000
508000
493000
490000
469000
478000
528000
534000
518000
506000
502000
516000
528000
533000
536000
537000
524000
536000
587000
597000
581000
564000
558000
575000

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=105717&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=105717&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105717&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
15842508057.0879768478818000
259650033080.709383768362000
360800015340.577998671833000
45842508808.1401744825419000
559800028971.250116854453000
658275028040.149785619963000
754200015979.153085609235000
853250032388.269481403366000
952325014453.949863849232000
1050200012727.922061357927000
1150225033490.048273081665000
125105007724.4201508376416000
135335004041.451884327389000
1456100036359.317925395773000
1556950010408.329997330723000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 584250 & 8057.08797684788 & 18000 \tabularnewline
2 & 596500 & 33080.7093837683 & 62000 \tabularnewline
3 & 608000 & 15340.5779986718 & 33000 \tabularnewline
4 & 584250 & 8808.14017448254 & 19000 \tabularnewline
5 & 598000 & 28971.2501168544 & 53000 \tabularnewline
6 & 582750 & 28040.1497856199 & 63000 \tabularnewline
7 & 542000 & 15979.1530856092 & 35000 \tabularnewline
8 & 532500 & 32388.2694814033 & 66000 \tabularnewline
9 & 523250 & 14453.9498638492 & 32000 \tabularnewline
10 & 502000 & 12727.9220613579 & 27000 \tabularnewline
11 & 502250 & 33490.0482730816 & 65000 \tabularnewline
12 & 510500 & 7724.42015083764 & 16000 \tabularnewline
13 & 533500 & 4041.45188432738 & 9000 \tabularnewline
14 & 561000 & 36359.3179253957 & 73000 \tabularnewline
15 & 569500 & 10408.3299973307 & 23000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105717&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]584250[/C][C]8057.08797684788[/C][C]18000[/C][/ROW]
[ROW][C]2[/C][C]596500[/C][C]33080.7093837683[/C][C]62000[/C][/ROW]
[ROW][C]3[/C][C]608000[/C][C]15340.5779986718[/C][C]33000[/C][/ROW]
[ROW][C]4[/C][C]584250[/C][C]8808.14017448254[/C][C]19000[/C][/ROW]
[ROW][C]5[/C][C]598000[/C][C]28971.2501168544[/C][C]53000[/C][/ROW]
[ROW][C]6[/C][C]582750[/C][C]28040.1497856199[/C][C]63000[/C][/ROW]
[ROW][C]7[/C][C]542000[/C][C]15979.1530856092[/C][C]35000[/C][/ROW]
[ROW][C]8[/C][C]532500[/C][C]32388.2694814033[/C][C]66000[/C][/ROW]
[ROW][C]9[/C][C]523250[/C][C]14453.9498638492[/C][C]32000[/C][/ROW]
[ROW][C]10[/C][C]502000[/C][C]12727.9220613579[/C][C]27000[/C][/ROW]
[ROW][C]11[/C][C]502250[/C][C]33490.0482730816[/C][C]65000[/C][/ROW]
[ROW][C]12[/C][C]510500[/C][C]7724.42015083764[/C][C]16000[/C][/ROW]
[ROW][C]13[/C][C]533500[/C][C]4041.45188432738[/C][C]9000[/C][/ROW]
[ROW][C]14[/C][C]561000[/C][C]36359.3179253957[/C][C]73000[/C][/ROW]
[ROW][C]15[/C][C]569500[/C][C]10408.3299973307[/C][C]23000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105717&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105717&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
15842508057.0879768478818000
259650033080.709383768362000
360800015340.577998671833000
45842508808.1401744825419000
559800028971.250116854453000
658275028040.149785619963000
754200015979.153085609235000
853250032388.269481403366000
952325014453.949863849232000
1050200012727.922061357927000
1150225033490.048273081665000
125105007724.4201508376416000
135335004041.451884327389000
1456100036359.317925395773000
1556950010408.329997330723000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1431.60585662623
beta0.0373752127497771
S.D.0.085119623784568
T-STAT0.439090436353093
p-value0.667805819745062

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1431.60585662623 \tabularnewline
beta & 0.0373752127497771 \tabularnewline
S.D. & 0.085119623784568 \tabularnewline
T-STAT & 0.439090436353093 \tabularnewline
p-value & 0.667805819745062 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105717&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1431.60585662623[/C][/ROW]
[ROW][C]beta[/C][C]0.0373752127497771[/C][/ROW]
[ROW][C]S.D.[/C][C]0.085119623784568[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.439090436353093[/C][/ROW]
[ROW][C]p-value[/C][C]0.667805819745062[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105717&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105717&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-1431.60585662623
beta0.0373752127497771
S.D.0.085119623784568
T-STAT0.439090436353093
p-value0.667805819745062






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-10.2674070044768
beta1.50807497646145
S.D.2.79305180990489
T-STAT0.539938060265629
p-value0.598367737940932
Lambda-0.508074976461448

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.2674070044768 \tabularnewline
beta & 1.50807497646145 \tabularnewline
S.D. & 2.79305180990489 \tabularnewline
T-STAT & 0.539938060265629 \tabularnewline
p-value & 0.598367737940932 \tabularnewline
Lambda & -0.508074976461448 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105717&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.2674070044768[/C][/ROW]
[ROW][C]beta[/C][C]1.50807497646145[/C][/ROW]
[ROW][C]S.D.[/C][C]2.79305180990489[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.539938060265629[/C][/ROW]
[ROW][C]p-value[/C][C]0.598367737940932[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.508074976461448[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105717&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105717&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-10.2674070044768
beta1.50807497646145
S.D.2.79305180990489
T-STAT0.539938060265629
p-value0.598367737940932
Lambda-0.508074976461448


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')