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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 computationSun, 19 Dec 2010 21:38:36 +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/19/t1292794601iuzrw7gk0jwsy37.htm/, Retrieved Sun, 05 May 2024 02:24:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112765, Retrieved Sun, 05 May 2024 02:24:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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, SMP] [2010-12-05 19:10:21] [3635fb7041b1998c5a1332cf9de22bce]
-    D      [Standard Deviation-Mean Plot] [Paper SDMP] [2010-12-19 16:22:55] [3635fb7041b1998c5a1332cf9de22bce]
-    D          [Standard Deviation-Mean Plot] [Paper SDMP 2] [2010-12-19 21:38:36] [23a9b79f355c69a75648521a893cf584] [Current]
-   P             [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-12-22 08:56:47] [8081b8996d5947580de3eb171e82db4f]
-                 [Standard Deviation-Mean Plot] [Paper Standard De...] [2010-12-22 14:21:43] [d946de7cca328fbcf207448a112523ab]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21.454
23.899
24.939
23.580
24.562
24.696
23.785
23.812
21.917
19.713
19.282
18.788
21.453
24.482
27.474
27.264
27.349
30.632
29.429
30.084
26.290
24.379
23.335
21.346
21.106
24.514
28.353
30.805
31.348
34.556
33.855
34.787
32.529
29.998
29.257
28.155
30.466
35.704
39.327
39.351
42.234
43.630
43.722
43.121
37.985
37.135
34.646
33.026
35.087
38.846
42.013
43.908
42.868
44.423
44.167
43.636
44.382
42.142
43.452
36.912
42.413
45.344
44.873
47.510
49.554
47.369
45.998
48.140
48.441
44.928
40.454
38.661
37.246
36.843
36.424
37.594
38.144
38.737
34.560
36.080
33.508
35.462
33.374
32.110

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112765&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112765&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
122.53558333333332.232809052550516.151
226.12641666666673.158597717006529.286
329.93858333333334.0811913915231213.681
438.362254.3627787668161513.256
541.81966666666673.143167925208689.336
645.30708333333333.3288943689605110.893
735.84016666666672.075235050578976.627

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22.5355833333333 & 2.23280905255051 & 6.151 \tabularnewline
2 & 26.1264166666667 & 3.15859771700652 & 9.286 \tabularnewline
3 & 29.9385833333333 & 4.08119139152312 & 13.681 \tabularnewline
4 & 38.36225 & 4.36277876681615 & 13.256 \tabularnewline
5 & 41.8196666666667 & 3.14316792520868 & 9.336 \tabularnewline
6 & 45.3070833333333 & 3.32889436896051 & 10.893 \tabularnewline
7 & 35.8401666666667 & 2.07523505057897 & 6.627 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112765&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]22.5355833333333[/C][C]2.23280905255051[/C][C]6.151[/C][/ROW]
[ROW][C]2[/C][C]26.1264166666667[/C][C]3.15859771700652[/C][C]9.286[/C][/ROW]
[ROW][C]3[/C][C]29.9385833333333[/C][C]4.08119139152312[/C][C]13.681[/C][/ROW]
[ROW][C]4[/C][C]38.36225[/C][C]4.36277876681615[/C][C]13.256[/C][/ROW]
[ROW][C]5[/C][C]41.8196666666667[/C][C]3.14316792520868[/C][C]9.336[/C][/ROW]
[ROW][C]6[/C][C]45.3070833333333[/C][C]3.32889436896051[/C][C]10.893[/C][/ROW]
[ROW][C]7[/C][C]35.8401666666667[/C][C]2.07523505057897[/C][C]6.627[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112765&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
122.53558333333332.232809052550516.151
226.12641666666673.158597717006529.286
329.93858333333334.0811913915231213.681
438.362254.3627787668161513.256
541.81966666666673.143167925208689.336
645.30708333333333.3288943689605110.893
735.84016666666672.075235050578976.627






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.23183648134051
beta0.0281741589080172
S.D.0.0436923281553852
T-STAT0.644830799764666
p-value0.54745237268799

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.23183648134051 \tabularnewline
beta & 0.0281741589080172 \tabularnewline
S.D. & 0.0436923281553852 \tabularnewline
T-STAT & 0.644830799764666 \tabularnewline
p-value & 0.54745237268799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112765&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.23183648134051[/C][/ROW]
[ROW][C]beta[/C][C]0.0281741589080172[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0436923281553852[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.644830799764666[/C][/ROW]
[ROW][C]p-value[/C][C]0.54745237268799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112765&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112765&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)
alpha2.23183648134051
beta0.0281741589080172
S.D.0.0436923281553852
T-STAT0.644830799764666
p-value0.54745237268799






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.098376343942758
beta0.350281451674038
S.D.0.46035039871782
T-STAT0.760901810120402
p-value0.481039562608995
Lambda0.649718548325962

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.098376343942758 \tabularnewline
beta & 0.350281451674038 \tabularnewline
S.D. & 0.46035039871782 \tabularnewline
T-STAT & 0.760901810120402 \tabularnewline
p-value & 0.481039562608995 \tabularnewline
Lambda & 0.649718548325962 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112765&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.098376343942758[/C][/ROW]
[ROW][C]beta[/C][C]0.350281451674038[/C][/ROW]
[ROW][C]S.D.[/C][C]0.46035039871782[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.760901810120402[/C][/ROW]
[ROW][C]p-value[/C][C]0.481039562608995[/C][/ROW]
[ROW][C]Lambda[/C][C]0.649718548325962[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112765&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112765&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-0.098376343942758
beta0.350281451674038
S.D.0.46035039871782
T-STAT0.760901810120402
p-value0.481039562608995
Lambda0.649718548325962


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')