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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 computationFri, 10 Dec 2010 15:22:34 +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/10/t1291994484z0xo3819mtzgx2y.htm/, Retrieved Mon, 29 Apr 2024 10:15:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107765, Retrieved Mon, 29 Apr 2024 10:15:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   PD    [Standard Deviation-Mean Plot] [workshop 9 - 6] [2010-12-03 17:08:19] [74be16979710d4c4e7c6647856088456]
-   PD        [Standard Deviation-Mean Plot] [paper - time-seri...] [2010-12-10 15:22:34] [6ea41cf020a5319fc3c331a4158019e5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
296.95
296.84
287.54 
287.81
283.99
275.79
269.52
278.35
283.43
289.46
282.30
293.55
304.78
300.99
315.29
316.21
331.79
329.38
317.27
317.98
340.28
339.21
336.71
340.11
347.72
328.68
303.05
299.83
320.04
317.94
303.31
308.85
319.19
314.52
312.39
315.77
320.23
309.45
296.54
297.28
301.39
306.68
305.91
314.76
323.34
341.58
330.12
318.16
317.84
325.39
327.56
329.77
333.29
346.10
358.00
344.82
313.30
301.26
306.38
319.31

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107765&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107765&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1292.2855.32449997652369.40999999999997
2276.91256.0018462437264614.4700000000000
3287.1855.280533432649911.25
4309.31757.5963472581673515.2200000000000
5324.1057.5524322792947614.5200000000000
6339.07751.646681005335693.56999999999999
7319.8222.640248820776447.89
8312.5357.8362171996442316.7300000000000
9315.46752.847061350468826.80000000000001
10305.87511.252598218485723.69
11307.1855.5630716934681613.37
12328.310.117509574989323.4200000000000
13325.145.1847790052550411.93
14345.552510.101905348332424.71
15310.06257.8960427852606518.05

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 292.285 & 5.3244999765236 & 9.40999999999997 \tabularnewline
2 & 276.9125 & 6.00184624372646 & 14.4700000000000 \tabularnewline
3 & 287.185 & 5.2805334326499 & 11.25 \tabularnewline
4 & 309.3175 & 7.59634725816735 & 15.2200000000000 \tabularnewline
5 & 324.105 & 7.55243227929476 & 14.5200000000000 \tabularnewline
6 & 339.0775 & 1.64668100533569 & 3.56999999999999 \tabularnewline
7 & 319.82 & 22.6402488207764 & 47.89 \tabularnewline
8 & 312.535 & 7.83621719964423 & 16.7300000000000 \tabularnewline
9 & 315.4675 & 2.84706135046882 & 6.80000000000001 \tabularnewline
10 & 305.875 & 11.2525982184857 & 23.69 \tabularnewline
11 & 307.185 & 5.56307169346816 & 13.37 \tabularnewline
12 & 328.3 & 10.1175095749893 & 23.4200000000000 \tabularnewline
13 & 325.14 & 5.18477900525504 & 11.93 \tabularnewline
14 & 345.5525 & 10.1019053483324 & 24.71 \tabularnewline
15 & 310.0625 & 7.89604278526065 & 18.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107765&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]292.285[/C][C]5.3244999765236[/C][C]9.40999999999997[/C][/ROW]
[ROW][C]2[/C][C]276.9125[/C][C]6.00184624372646[/C][C]14.4700000000000[/C][/ROW]
[ROW][C]3[/C][C]287.185[/C][C]5.2805334326499[/C][C]11.25[/C][/ROW]
[ROW][C]4[/C][C]309.3175[/C][C]7.59634725816735[/C][C]15.2200000000000[/C][/ROW]
[ROW][C]5[/C][C]324.105[/C][C]7.55243227929476[/C][C]14.5200000000000[/C][/ROW]
[ROW][C]6[/C][C]339.0775[/C][C]1.64668100533569[/C][C]3.56999999999999[/C][/ROW]
[ROW][C]7[/C][C]319.82[/C][C]22.6402488207764[/C][C]47.89[/C][/ROW]
[ROW][C]8[/C][C]312.535[/C][C]7.83621719964423[/C][C]16.7300000000000[/C][/ROW]
[ROW][C]9[/C][C]315.4675[/C][C]2.84706135046882[/C][C]6.80000000000001[/C][/ROW]
[ROW][C]10[/C][C]305.875[/C][C]11.2525982184857[/C][C]23.69[/C][/ROW]
[ROW][C]11[/C][C]307.185[/C][C]5.56307169346816[/C][C]13.37[/C][/ROW]
[ROW][C]12[/C][C]328.3[/C][C]10.1175095749893[/C][C]23.4200000000000[/C][/ROW]
[ROW][C]13[/C][C]325.14[/C][C]5.18477900525504[/C][C]11.93[/C][/ROW]
[ROW][C]14[/C][C]345.5525[/C][C]10.1019053483324[/C][C]24.71[/C][/ROW]
[ROW][C]15[/C][C]310.0625[/C][C]7.89604278526065[/C][C]18.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107765&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
1292.2855.32449997652369.40999999999997
2276.91256.0018462437264614.4700000000000
3287.1855.280533432649911.25
4309.31757.5963472581673515.2200000000000
5324.1057.5524322792947614.5200000000000
6339.07751.646681005335693.56999999999999
7319.8222.640248820776447.89
8312.5357.8362171996442316.7300000000000
9315.46752.847061350468826.80000000000001
10305.87511.252598218485723.69
11307.1855.5630716934681613.37
12328.310.117509574989323.4200000000000
13325.145.1847790052550411.93
14345.552510.101905348332424.71
15310.06257.8960427852606518.05






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-3.59830844805323
beta0.0363530420218644
S.D.0.0723321989224206
T-STAT0.502584499896853
p-value0.623662176193751

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.59830844805323 \tabularnewline
beta & 0.0363530420218644 \tabularnewline
S.D. & 0.0723321989224206 \tabularnewline
T-STAT & 0.502584499896853 \tabularnewline
p-value & 0.623662176193751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107765&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.59830844805323[/C][/ROW]
[ROW][C]beta[/C][C]0.0363530420218644[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0723321989224206[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.502584499896853[/C][/ROW]
[ROW][C]p-value[/C][C]0.623662176193751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107765&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107765&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-3.59830844805323
beta0.0363530420218644
S.D.0.0723321989224206
T-STAT0.502584499896853
p-value0.623662176193751






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.91511151320340
beta-0.00405379362174322
S.D.2.80306229121872
T-STAT-0.00144620176099644
p-value0.998868055466292
Lambda1.00405379362174

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.91511151320340 \tabularnewline
beta & -0.00405379362174322 \tabularnewline
S.D. & 2.80306229121872 \tabularnewline
T-STAT & -0.00144620176099644 \tabularnewline
p-value & 0.998868055466292 \tabularnewline
Lambda & 1.00405379362174 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107765&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.91511151320340[/C][/ROW]
[ROW][C]beta[/C][C]-0.00405379362174322[/C][/ROW]
[ROW][C]S.D.[/C][C]2.80306229121872[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.00144620176099644[/C][/ROW]
[ROW][C]p-value[/C][C]0.998868055466292[/C][/ROW]
[ROW][C]Lambda[/C][C]1.00405379362174[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107765&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107765&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)
alpha1.91511151320340
beta-0.00405379362174322
S.D.2.80306229121872
T-STAT-0.00144620176099644
p-value0.998868055466292
Lambda1.00405379362174


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')