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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 computationMon, 13 Dec 2010 13:44:24 +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/13/t1292247775f0v4kpex4vpuncf.htm/, Retrieved Mon, 06 May 2024 20:57:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108916, Retrieved Mon, 06 May 2024 20:57:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper DMA
Estimated Impact129

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD  [Variance Reduction Matrix] [VRM WS9] [2010-12-06 11:58:32] [f4dc4aa51d65be851b8508203d9f6001]
- R PD    [Variance Reduction Matrix] [] [2010-12-06 17:10:58] [d39e5c40c631ed6c22677d2e41dbfc7d]
- RMPD        [Standard Deviation-Mean Plot] [Paper DMA SMP] [2010-12-13 13:44:24] [f92ba2b01007f169e2985fcc57236bd0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030,29
2803,47
2767,63
2882,6
2863,36
2897,06
3012,61
3142,95
3032,93
3045,78
3110,52
3013,24
2987,1
2995,55
2833,18
2848,96
2794,83
2845,26
2915,03
2892,63
2604,42
2641,65
2659,81
2638,53
2720,25
2745,88
2735,7
2811,7
2799,43
2555,28
2304,98
2214,95
2065,81
1940,49
2042
1995,37
1946,81
1765,9
1635,25
1833,42
1910,43
1959,67
1969,6
2061,41
2093,48
2120,88
2174,56
2196,72
2350,44
2440,25
2408,64
2472,81
2407,6
2454,62
2448,05
2497,84
2645,64
2756,76
2849,27
2921,44
2981,85
3080,58
3106,22
3119,31
3061,26
3097,31
3161,69
3257,16
3277,01
3295,32
3363,99
3494,17
3667,03
3813,06
3917,96
3895,51
3801,06
3570,12
3701,61
3862,27
3970,1
4138,52
4199,75
4290,89
4443,91
4502,64
4356,98
4591,27
4696,96
4621,4
4562,84
4202,52
4296,49
4435,23
4105,18
4116,68
3844,49
3720,98
3674,4
3857,62
3801,06
3504,37
3032,6
3047,03
2962,34
2197,82
2014,45
1862,83
1905,41

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108916&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]2 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=108916&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108916&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12966.87120.446120810020375.32
22804.74583333333137.976744249848391.13
32410.98666666667349.621389254494871.21
41972.34416666667169.520817249860561.47
52554.44666666667190.570772791696571
63191.3225147.471609663753512.32
73902.32333333333218.664223632879720.77
84411.00833333333198.014401580626591.78
93126.66583333333740.9765292376411994.79

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2966.87 & 120.446120810020 & 375.32 \tabularnewline
2 & 2804.74583333333 & 137.976744249848 & 391.13 \tabularnewline
3 & 2410.98666666667 & 349.621389254494 & 871.21 \tabularnewline
4 & 1972.34416666667 & 169.520817249860 & 561.47 \tabularnewline
5 & 2554.44666666667 & 190.570772791696 & 571 \tabularnewline
6 & 3191.3225 & 147.471609663753 & 512.32 \tabularnewline
7 & 3902.32333333333 & 218.664223632879 & 720.77 \tabularnewline
8 & 4411.00833333333 & 198.014401580626 & 591.78 \tabularnewline
9 & 3126.66583333333 & 740.976529237641 & 1994.79 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108916&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]2966.87[/C][C]120.446120810020[/C][C]375.32[/C][/ROW]
[ROW][C]2[/C][C]2804.74583333333[/C][C]137.976744249848[/C][C]391.13[/C][/ROW]
[ROW][C]3[/C][C]2410.98666666667[/C][C]349.621389254494[/C][C]871.21[/C][/ROW]
[ROW][C]4[/C][C]1972.34416666667[/C][C]169.520817249860[/C][C]561.47[/C][/ROW]
[ROW][C]5[/C][C]2554.44666666667[/C][C]190.570772791696[/C][C]571[/C][/ROW]
[ROW][C]6[/C][C]3191.3225[/C][C]147.471609663753[/C][C]512.32[/C][/ROW]
[ROW][C]7[/C][C]3902.32333333333[/C][C]218.664223632879[/C][C]720.77[/C][/ROW]
[ROW][C]8[/C][C]4411.00833333333[/C][C]198.014401580626[/C][C]591.78[/C][/ROW]
[ROW][C]9[/C][C]3126.66583333333[/C][C]740.976529237641[/C][C]1994.79[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108916&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108916&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
12966.87120.446120810020375.32
22804.74583333333137.976744249848391.13
32410.98666666667349.621389254494871.21
41972.34416666667169.520817249860561.47
52554.44666666667190.570772791696571
63191.3225147.471609663753512.32
73902.32333333333218.664223632879720.77
84411.00833333333198.014401580626591.78
93126.66583333333740.9765292376411994.79






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha241.249890765477
beta0.00373119714682620
S.D.0.0984600929728486
T-STAT0.0378955273570086
p-value0.970829070950793

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 241.249890765477 \tabularnewline
beta & 0.00373119714682620 \tabularnewline
S.D. & 0.0984600929728486 \tabularnewline
T-STAT & 0.0378955273570086 \tabularnewline
p-value & 0.970829070950793 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108916&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]241.249890765477[/C][/ROW]
[ROW][C]beta[/C][C]0.00373119714682620[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0984600929728486[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0378955273570086[/C][/ROW]
[ROW][C]p-value[/C][C]0.970829070950793[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108916&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108916&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)
alpha241.249890765477
beta0.00373119714682620
S.D.0.0984600929728486
T-STAT0.0378955273570086
p-value0.970829070950793






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.54866900862879
beta0.101451645607604
S.D.0.868911365799988
T-STAT0.116757185601088
p-value0.910331721992732
Lambda0.898548354392396

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.54866900862879 \tabularnewline
beta & 0.101451645607604 \tabularnewline
S.D. & 0.868911365799988 \tabularnewline
T-STAT & 0.116757185601088 \tabularnewline
p-value & 0.910331721992732 \tabularnewline
Lambda & 0.898548354392396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108916&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.54866900862879[/C][/ROW]
[ROW][C]beta[/C][C]0.101451645607604[/C][/ROW]
[ROW][C]S.D.[/C][C]0.868911365799988[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.116757185601088[/C][/ROW]
[ROW][C]p-value[/C][C]0.910331721992732[/C][/ROW]
[ROW][C]Lambda[/C][C]0.898548354392396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108916&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108916&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)
alpha4.54866900862879
beta0.101451645607604
S.D.0.868911365799988
T-STAT0.116757185601088
p-value0.910331721992732
Lambda0.898548354392396


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')