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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, 28 Dec 2010 14:01:20 +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/28/t1293544819uqr669er0kbmvkw.htm/, Retrieved Sun, 05 May 2024 01:01:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116365, Retrieved Sun, 05 May 2024 01:01:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsStandard Deviation Mean Plot - Handelsbalans België (1995-2009)
Estimated Impact103

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] [Paper Statistiek] [2010-12-28 09:04:37] [82c18f3ebe9df70882495121eb816e07]
-    D    [Standard Deviation-Mean Plot] [Paper Statistiek] [2010-12-28 14:01:20] [f6fdc0236f011c1845380977efc505f8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2540,9
2370,3
1807,5
1834,8
786,8
1561,4
1347,2
1549,8
1553,8
1822,5
3078,7
1589,1
1791,5
2558,1
2111,8
2083,1
2052,1
2243,5
2622
1952,6
808,9
1709,8
1582,1
865,6
1116,1
1119,4
2350
1975,6
2536,5
2785
2819,7
1829,5
758,3
2921,6
2482
1892,7
1855,1
2151,3
1642,2
1640,5
1366,1
1532,8
824,4
-518,7
-978,5
1162,5
1243,4
1199,5
883,1
1437,2
534,5
-1901,9
-2521,1
-1721,1
-3094,5
-3694,8
-2492,1
-464,6
-626,1
-1711,4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 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 & 11 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116365&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]11 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=116365&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116365&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 time11 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12138.375373.028876228101733.4
21311.3363.236066491201774.6
32011.025721.6986877037631524.9
42136.125316.350358252787766.6
52217.55295.423656240773669.4
61241.6470.37459540243900.9
71640.275622.4207118179791233.9
82492.675459.753907904363990.2
92013.65937.0623333944582163.3
101822.275241.387715442743510.8
11801.15930.416539334222051.5
12656.7251090.651396719722221.9
13238.2251474.372036665103339.1
14-2757.875841.0528416811871973.7
15-1323.55955.714101252742027.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2138.375 & 373.028876228101 & 733.4 \tabularnewline
2 & 1311.3 & 363.236066491201 & 774.6 \tabularnewline
3 & 2011.025 & 721.698687703763 & 1524.9 \tabularnewline
4 & 2136.125 & 316.350358252787 & 766.6 \tabularnewline
5 & 2217.55 & 295.423656240773 & 669.4 \tabularnewline
6 & 1241.6 & 470.37459540243 & 900.9 \tabularnewline
7 & 1640.275 & 622.420711817979 & 1233.9 \tabularnewline
8 & 2492.675 & 459.753907904363 & 990.2 \tabularnewline
9 & 2013.65 & 937.062333394458 & 2163.3 \tabularnewline
10 & 1822.275 & 241.387715442743 & 510.8 \tabularnewline
11 & 801.15 & 930.41653933422 & 2051.5 \tabularnewline
12 & 656.725 & 1090.65139671972 & 2221.9 \tabularnewline
13 & 238.225 & 1474.37203666510 & 3339.1 \tabularnewline
14 & -2757.875 & 841.052841681187 & 1973.7 \tabularnewline
15 & -1323.55 & 955.71410125274 & 2027.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116365&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]2138.375[/C][C]373.028876228101[/C][C]733.4[/C][/ROW]
[ROW][C]2[/C][C]1311.3[/C][C]363.236066491201[/C][C]774.6[/C][/ROW]
[ROW][C]3[/C][C]2011.025[/C][C]721.698687703763[/C][C]1524.9[/C][/ROW]
[ROW][C]4[/C][C]2136.125[/C][C]316.350358252787[/C][C]766.6[/C][/ROW]
[ROW][C]5[/C][C]2217.55[/C][C]295.423656240773[/C][C]669.4[/C][/ROW]
[ROW][C]6[/C][C]1241.6[/C][C]470.37459540243[/C][C]900.9[/C][/ROW]
[ROW][C]7[/C][C]1640.275[/C][C]622.420711817979[/C][C]1233.9[/C][/ROW]
[ROW][C]8[/C][C]2492.675[/C][C]459.753907904363[/C][C]990.2[/C][/ROW]
[ROW][C]9[/C][C]2013.65[/C][C]937.062333394458[/C][C]2163.3[/C][/ROW]
[ROW][C]10[/C][C]1822.275[/C][C]241.387715442743[/C][C]510.8[/C][/ROW]
[ROW][C]11[/C][C]801.15[/C][C]930.41653933422[/C][C]2051.5[/C][/ROW]
[ROW][C]12[/C][C]656.725[/C][C]1090.65139671972[/C][C]2221.9[/C][/ROW]
[ROW][C]13[/C][C]238.225[/C][C]1474.37203666510[/C][C]3339.1[/C][/ROW]
[ROW][C]14[/C][C]-2757.875[/C][C]841.052841681187[/C][C]1973.7[/C][/ROW]
[ROW][C]15[/C][C]-1323.55[/C][C]955.71410125274[/C][C]2027.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116365&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116365&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
12138.375373.028876228101733.4
21311.3363.236066491201774.6
32011.025721.6986877037631524.9
42136.125316.350358252787766.6
52217.55295.423656240773669.4
61241.6470.37459540243900.9
71640.275622.4207118179791233.9
82492.675459.753907904363990.2
92013.65937.0623333944582163.3
101822.275241.387715442743510.8
11801.15930.416539334222051.5
12656.7251090.651396719722221.9
13238.2251474.372036665103339.1
14-2757.875841.0528416811871973.7
15-1323.55955.714101252742027.5






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha816.210526139314
beta-0.129223284171762
S.D.0.0580319958872454
T-STAT-2.22675925919969
p-value0.0442644742863094

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 816.210526139314 \tabularnewline
beta & -0.129223284171762 \tabularnewline
S.D. & 0.0580319958872454 \tabularnewline
T-STAT & -2.22675925919969 \tabularnewline
p-value & 0.0442644742863094 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116365&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]816.210526139314[/C][/ROW]
[ROW][C]beta[/C][C]-0.129223284171762[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0580319958872454[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.22675925919969[/C][/ROW]
[ROW][C]p-value[/C][C]0.0442644742863094[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116365&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116365&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)
alpha816.210526139314
beta-0.129223284171762
S.D.0.0580319958872454
T-STAT-2.22675925919969
p-value0.0442644742863094






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha10.6824183728588
beta-0.605263424427792
S.D.0.180617347388167
T-STAT-3.35108135060257
p-value0.00646519510211228
Lambda1.60526342442779

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 10.6824183728588 \tabularnewline
beta & -0.605263424427792 \tabularnewline
S.D. & 0.180617347388167 \tabularnewline
T-STAT & -3.35108135060257 \tabularnewline
p-value & 0.00646519510211228 \tabularnewline
Lambda & 1.60526342442779 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116365&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.6824183728588[/C][/ROW]
[ROW][C]beta[/C][C]-0.605263424427792[/C][/ROW]
[ROW][C]S.D.[/C][C]0.180617347388167[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.35108135060257[/C][/ROW]
[ROW][C]p-value[/C][C]0.00646519510211228[/C][/ROW]
[ROW][C]Lambda[/C][C]1.60526342442779[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116365&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116365&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)
alpha10.6824183728588
beta-0.605263424427792
S.D.0.180617347388167
T-STAT-3.35108135060257
p-value0.00646519510211228
Lambda1.60526342442779


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')