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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 computationSat, 25 Dec 2010 18:12:17 +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/25/t12933005906v7292bkfearbqg.htm/, Retrieved Sun, 28 Apr 2024 22:38:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115430, Retrieved Sun, 28 Apr 2024 22:38:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

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]
-   PD      [Standard Deviation-Mean Plot] [smp] [2010-12-21 15:12:54] [f9eaed74daea918f73b9f505c5b1f19e]
-   PD          [Standard Deviation-Mean Plot] [SMP (olieprijzen)] [2010-12-25 18:12:17] [2e49bff66bb3e1f5d7fa8957e12fbb12] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.22
27.63
27.47
22.54
27.4
29.68
28.51
29.89
32.62
30.93
32.52
25.28
25.64
27.41
24.4
25.55
28.45
27.72
24.54
25.67
25.54
20.48
18.94
18.6
19.49
20.29
23.69
25.65
25.43
24.13
25.77
26.63
28.34
27.55
24.5
28.52
31.29
32.65
30.34
25.02
25.81
27.55
28.4
29.83
27.1
29.59
28.77
29.88
31.18
30.87
33.8
33.36
37.92
35.19
38.37
43.03
43.38
49.77
43.05
39.65
44.28
45.56
53.08
51.86
48.67
54.31
57.58
64.09
62.98
58.52
55.54
56.75
63.57
59.92
62.25
70.44
70.19
68.86
73.9
73.61
62.77
58.38
58.48
62.31
54.3
57.76
62.14
67.4
67.48
71.32
77.2
70.8
77.13
83.04
92.53
91.45
91.92
94.82
103.28
110.44
123.94
133.05
133.9
113.85
99.06
72.84
53.24
41.58
44.86
43.24
46.84
50.85
57.94
68.59
64.92
72.5
67.69
73.19
77.04
74.67

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115430&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115430&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115430&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
128.30753.039076190375810.08
224.41166666666673.31790687943569.85
324.99916666666672.847213816198489.03
428.85252.21676309883667.63
538.29755.7564148012140718.9
654.4356.2011853705561819.81
765.395.6961214874684715.52
872.712512.156965923064338.23
997.6629.373094367588792.32
1061.860833333333312.514150868904233.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 28.3075 & 3.0390761903758 & 10.08 \tabularnewline
2 & 24.4116666666667 & 3.3179068794356 & 9.85 \tabularnewline
3 & 24.9991666666667 & 2.84721381619848 & 9.03 \tabularnewline
4 & 28.8525 & 2.2167630988366 & 7.63 \tabularnewline
5 & 38.2975 & 5.75641480121407 & 18.9 \tabularnewline
6 & 54.435 & 6.20118537055618 & 19.81 \tabularnewline
7 & 65.39 & 5.69612148746847 & 15.52 \tabularnewline
8 & 72.7125 & 12.1569659230643 & 38.23 \tabularnewline
9 & 97.66 & 29.3730943675887 & 92.32 \tabularnewline
10 & 61.8608333333333 & 12.5141508689042 & 33.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115430&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]28.3075[/C][C]3.0390761903758[/C][C]10.08[/C][/ROW]
[ROW][C]2[/C][C]24.4116666666667[/C][C]3.3179068794356[/C][C]9.85[/C][/ROW]
[ROW][C]3[/C][C]24.9991666666667[/C][C]2.84721381619848[/C][C]9.03[/C][/ROW]
[ROW][C]4[/C][C]28.8525[/C][C]2.2167630988366[/C][C]7.63[/C][/ROW]
[ROW][C]5[/C][C]38.2975[/C][C]5.75641480121407[/C][C]18.9[/C][/ROW]
[ROW][C]6[/C][C]54.435[/C][C]6.20118537055618[/C][C]19.81[/C][/ROW]
[ROW][C]7[/C][C]65.39[/C][C]5.69612148746847[/C][C]15.52[/C][/ROW]
[ROW][C]8[/C][C]72.7125[/C][C]12.1569659230643[/C][C]38.23[/C][/ROW]
[ROW][C]9[/C][C]97.66[/C][C]29.3730943675887[/C][C]92.32[/C][/ROW]
[ROW][C]10[/C][C]61.8608333333333[/C][C]12.5141508689042[/C][C]33.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115430&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115430&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
128.30753.039076190375810.08
224.41166666666673.31790687943569.85
324.99916666666672.847213816198489.03
428.85252.21676309883667.63
538.29755.7564148012140718.9
654.4356.2011853705561819.81
765.395.6961214874684715.52
872.712512.156965923064338.23
997.6629.373094367588792.32
1061.860833333333312.514150868904233.8






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-6.35715766543573
beta0.295195406682407
S.D.0.0548374215846091
T-STAT5.38310150536432
p-value0.000659188234069767

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -6.35715766543573 \tabularnewline
beta & 0.295195406682407 \tabularnewline
S.D. & 0.0548374215846091 \tabularnewline
T-STAT & 5.38310150536432 \tabularnewline
p-value & 0.000659188234069767 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115430&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.35715766543573[/C][/ROW]
[ROW][C]beta[/C][C]0.295195406682407[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0548374215846091[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.38310150536432[/C][/ROW]
[ROW][C]p-value[/C][C]0.000659188234069767[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115430&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115430&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-6.35715766543573
beta0.295195406682407
S.D.0.0548374215846091
T-STAT5.38310150536432
p-value0.000659188234069767






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.83370458379202
beta1.48174986693568
S.D.0.229850748075903
T-STAT6.44657404572104
p-value0.000199032246838031
Lambda-0.481749866935681

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.83370458379202 \tabularnewline
beta & 1.48174986693568 \tabularnewline
S.D. & 0.229850748075903 \tabularnewline
T-STAT & 6.44657404572104 \tabularnewline
p-value & 0.000199032246838031 \tabularnewline
Lambda & -0.481749866935681 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115430&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.83370458379202[/C][/ROW]
[ROW][C]beta[/C][C]1.48174986693568[/C][/ROW]
[ROW][C]S.D.[/C][C]0.229850748075903[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.44657404572104[/C][/ROW]
[ROW][C]p-value[/C][C]0.000199032246838031[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.481749866935681[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115430&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115430&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-3.83370458379202
beta1.48174986693568
S.D.0.229850748075903
T-STAT6.44657404572104
p-value0.000199032246838031
Lambda-0.481749866935681


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')