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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 26 May 2010 13:29:28 +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/May/26/t1274880611ghz0yt6cnew1scm.htm/, Retrieved Fri, 03 May 2024 03:52:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76489, Retrieved Fri, 03 May 2024 03:52:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact140

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation Plot] [Oefening 8 Opgave 2] [2010-05-26 12:31:25] [e895dcb2cc7dd335cb0a684691a903a1]
- RMPD    [Standard Deviation-Mean Plot] [Opgave 8 Oefening...] [2010-05-26 13:29:28] [f4bf273528b73565e5447b2f69f47b50] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22577.0
22792.0
23932.0
22321.0
21102.0
22824.0
23129.0
23604.0
24746.0
26911.0
27909.0
28922.0
29800.0
30506.0
30771.0
31976.0
33749.0
34371.0
33246.0
35072.0
35762.0
36179.0
37433.0
38298.0
37559.0
37511.0
39364.0
40084.0
42712.0
41938.0
40799.0
38568.0
41134.0
43955.0
43607.0
45082.0
46464.0
46496.0
46774.0
47890.0
45740.0
42660.0
39190.0
39010.0
41150.0
42530.0
44710.0
46620.0
44560.0
46120.0
48060.0
51970.0
57720.0
63490.0
65370.0
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58700.0
58630.0
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59266.0
60570.0
63062.0
63846.0
64726.0
63460.0
65220.0
66659.0
66871.0
65672.0
67182.0
68292.0
68318.0
69530.0
70500.0
72044.0
73811.0
76018.0
77818.0
79455.0
81408.0
81815.0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76489&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]1 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=76489&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76489&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
122905.5710.900133633411611
222664.751090.147811078852502
3271221784.121258958224176
430763.25906.4308670089892176
534109.5789.5950438885321826
6369181162.193615539172536
738629.51297.699631399092573
841004.251804.230283712884144
943444.51664.01452317383948
1046906670.6076846164731426
11416503202.571883138096730
1243752.52408.794650165655470
1347677.53199.816400983037410
14627103414.996339675937650
1559099.75548.5328157913621173
16630511788.214379392664156
1765552.51576.060172286163411
18673661247.300017370852646
1971471.251872.097820627974281
2078674.752300.129470993615390

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22905.5 & 710.90013363341 & 1611 \tabularnewline
2 & 22664.75 & 1090.14781107885 & 2502 \tabularnewline
3 & 27122 & 1784.12125895822 & 4176 \tabularnewline
4 & 30763.25 & 906.430867008989 & 2176 \tabularnewline
5 & 34109.5 & 789.595043888532 & 1826 \tabularnewline
6 & 36918 & 1162.19361553917 & 2536 \tabularnewline
7 & 38629.5 & 1297.69963139909 & 2573 \tabularnewline
8 & 41004.25 & 1804.23028371288 & 4144 \tabularnewline
9 & 43444.5 & 1664.0145231738 & 3948 \tabularnewline
10 & 46906 & 670.607684616473 & 1426 \tabularnewline
11 & 41650 & 3202.57188313809 & 6730 \tabularnewline
12 & 43752.5 & 2408.79465016565 & 5470 \tabularnewline
13 & 47677.5 & 3199.81640098303 & 7410 \tabularnewline
14 & 62710 & 3414.99633967593 & 7650 \tabularnewline
15 & 59099.75 & 548.532815791362 & 1173 \tabularnewline
16 & 63051 & 1788.21437939266 & 4156 \tabularnewline
17 & 65552.5 & 1576.06017228616 & 3411 \tabularnewline
18 & 67366 & 1247.30001737085 & 2646 \tabularnewline
19 & 71471.25 & 1872.09782062797 & 4281 \tabularnewline
20 & 78674.75 & 2300.12947099361 & 5390 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76489&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]22905.5[/C][C]710.90013363341[/C][C]1611[/C][/ROW]
[ROW][C]2[/C][C]22664.75[/C][C]1090.14781107885[/C][C]2502[/C][/ROW]
[ROW][C]3[/C][C]27122[/C][C]1784.12125895822[/C][C]4176[/C][/ROW]
[ROW][C]4[/C][C]30763.25[/C][C]906.430867008989[/C][C]2176[/C][/ROW]
[ROW][C]5[/C][C]34109.5[/C][C]789.595043888532[/C][C]1826[/C][/ROW]
[ROW][C]6[/C][C]36918[/C][C]1162.19361553917[/C][C]2536[/C][/ROW]
[ROW][C]7[/C][C]38629.5[/C][C]1297.69963139909[/C][C]2573[/C][/ROW]
[ROW][C]8[/C][C]41004.25[/C][C]1804.23028371288[/C][C]4144[/C][/ROW]
[ROW][C]9[/C][C]43444.5[/C][C]1664.0145231738[/C][C]3948[/C][/ROW]
[ROW][C]10[/C][C]46906[/C][C]670.607684616473[/C][C]1426[/C][/ROW]
[ROW][C]11[/C][C]41650[/C][C]3202.57188313809[/C][C]6730[/C][/ROW]
[ROW][C]12[/C][C]43752.5[/C][C]2408.79465016565[/C][C]5470[/C][/ROW]
[ROW][C]13[/C][C]47677.5[/C][C]3199.81640098303[/C][C]7410[/C][/ROW]
[ROW][C]14[/C][C]62710[/C][C]3414.99633967593[/C][C]7650[/C][/ROW]
[ROW][C]15[/C][C]59099.75[/C][C]548.532815791362[/C][C]1173[/C][/ROW]
[ROW][C]16[/C][C]63051[/C][C]1788.21437939266[/C][C]4156[/C][/ROW]
[ROW][C]17[/C][C]65552.5[/C][C]1576.06017228616[/C][C]3411[/C][/ROW]
[ROW][C]18[/C][C]67366[/C][C]1247.30001737085[/C][C]2646[/C][/ROW]
[ROW][C]19[/C][C]71471.25[/C][C]1872.09782062797[/C][C]4281[/C][/ROW]
[ROW][C]20[/C][C]78674.75[/C][C]2300.12947099361[/C][C]5390[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76489&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76489&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
122905.5710.900133633411611
222664.751090.147811078852502
3271221784.121258958224176
430763.25906.4308670089892176
534109.5789.5950438885321826
6369181162.193615539172536
738629.51297.699631399092573
841004.251804.230283712884144
943444.51664.01452317383948
1046906670.6076846164731426
11416503202.571883138096730
1243752.52408.794650165655470
1347677.53199.816400983037410
14627103414.996339675937650
1559099.75548.5328157913621173
16630511788.214379392664156
1765552.51576.060172286163411
18673661247.300017370852646
1971471.251872.097820627974281
2078674.752300.129470993615390






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha891.512731905937
beta0.0165083597516755
S.D.0.0116100711284143
T-STAT1.42189996676878
p-value0.172151949260523

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 891.512731905937 \tabularnewline
beta & 0.0165083597516755 \tabularnewline
S.D. & 0.0116100711284143 \tabularnewline
T-STAT & 1.42189996676878 \tabularnewline
p-value & 0.172151949260523 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76489&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]891.512731905937[/C][/ROW]
[ROW][C]beta[/C][C]0.0165083597516755[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0116100711284143[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.42189996676878[/C][/ROW]
[ROW][C]p-value[/C][C]0.172151949260523[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76489&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76489&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)
alpha891.512731905937
beta0.0165083597516755
S.D.0.0116100711284143
T-STAT1.42189996676878
p-value0.172151949260523






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.83472891519205
beta0.509817613569336
S.D.0.319629963525949
T-STAT1.59502447125220
p-value0.128114194333852
Lambda0.490182386430664

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.83472891519205 \tabularnewline
beta & 0.509817613569336 \tabularnewline
S.D. & 0.319629963525949 \tabularnewline
T-STAT & 1.59502447125220 \tabularnewline
p-value & 0.128114194333852 \tabularnewline
Lambda & 0.490182386430664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76489&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.83472891519205[/C][/ROW]
[ROW][C]beta[/C][C]0.509817613569336[/C][/ROW]
[ROW][C]S.D.[/C][C]0.319629963525949[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.59502447125220[/C][/ROW]
[ROW][C]p-value[/C][C]0.128114194333852[/C][/ROW]
[ROW][C]Lambda[/C][C]0.490182386430664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76489&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76489&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)
alpha1.83472891519205
beta0.509817613569336
S.D.0.319629963525949
T-STAT1.59502447125220
p-value0.128114194333852
Lambda0.490182386430664


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')