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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 computationMon, 05 Dec 2011 14:05:47 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/05/t13231119658v5g1nov5y0dmcg.htm/, Retrieved Fri, 03 May 2024 14:19:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151182, Retrieved Fri, 03 May 2024 14:19:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact95

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] [Bestellingen Boeing] [2011-12-05 19:05:47] [e09593412f775de82555261d5bbd0b3f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
20
32
11
14
199
162
88
89
24
36
142
193
39
25
95
144
33
131
31
24
160
52
57
210
13
52
96
133
74
131
129
74
127
55
175
185
34
115
95
58
63
56
70
32
32
14
6
23
18
4
6
17
20
20
44
32
20
14
9
59
10
47
43
34
5
49
130
10
117
108
17
55

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151182&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151182&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151182&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
119.259.2870878105033521
2134.555.2237871452752111
398.7582.2166852490012169
475.7554.6343908785178119
554.7550.9795710718192107
6119.7578.0870241034535158
773.552.182372502599120
810232.341923257592557
9135.559.3380147965872130
1075.536.373066958946481
1155.2516.520189667999238
1218.7511.236102527122126
1311.257.2743842809317314
142911.489125293076124
1525.522.78157149978950
1633.516.58312395177737
1748.557.7840808527747125
1874.2546.9565401905492100

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 19.25 & 9.28708781050335 & 21 \tabularnewline
2 & 134.5 & 55.2237871452752 & 111 \tabularnewline
3 & 98.75 & 82.2166852490012 & 169 \tabularnewline
4 & 75.75 & 54.6343908785178 & 119 \tabularnewline
5 & 54.75 & 50.9795710718192 & 107 \tabularnewline
6 & 119.75 & 78.0870241034535 & 158 \tabularnewline
7 & 73.5 & 52.182372502599 & 120 \tabularnewline
8 & 102 & 32.3419232575925 & 57 \tabularnewline
9 & 135.5 & 59.3380147965872 & 130 \tabularnewline
10 & 75.5 & 36.3730669589464 & 81 \tabularnewline
11 & 55.25 & 16.5201896679992 & 38 \tabularnewline
12 & 18.75 & 11.2361025271221 & 26 \tabularnewline
13 & 11.25 & 7.27438428093173 & 14 \tabularnewline
14 & 29 & 11.4891252930761 & 24 \tabularnewline
15 & 25.5 & 22.781571499789 & 50 \tabularnewline
16 & 33.5 & 16.583123951777 & 37 \tabularnewline
17 & 48.5 & 57.7840808527747 & 125 \tabularnewline
18 & 74.25 & 46.9565401905492 & 100 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151182&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]19.25[/C][C]9.28708781050335[/C][C]21[/C][/ROW]
[ROW][C]2[/C][C]134.5[/C][C]55.2237871452752[/C][C]111[/C][/ROW]
[ROW][C]3[/C][C]98.75[/C][C]82.2166852490012[/C][C]169[/C][/ROW]
[ROW][C]4[/C][C]75.75[/C][C]54.6343908785178[/C][C]119[/C][/ROW]
[ROW][C]5[/C][C]54.75[/C][C]50.9795710718192[/C][C]107[/C][/ROW]
[ROW][C]6[/C][C]119.75[/C][C]78.0870241034535[/C][C]158[/C][/ROW]
[ROW][C]7[/C][C]73.5[/C][C]52.182372502599[/C][C]120[/C][/ROW]
[ROW][C]8[/C][C]102[/C][C]32.3419232575925[/C][C]57[/C][/ROW]
[ROW][C]9[/C][C]135.5[/C][C]59.3380147965872[/C][C]130[/C][/ROW]
[ROW][C]10[/C][C]75.5[/C][C]36.3730669589464[/C][C]81[/C][/ROW]
[ROW][C]11[/C][C]55.25[/C][C]16.5201896679992[/C][C]38[/C][/ROW]
[ROW][C]12[/C][C]18.75[/C][C]11.2361025271221[/C][C]26[/C][/ROW]
[ROW][C]13[/C][C]11.25[/C][C]7.27438428093173[/C][C]14[/C][/ROW]
[ROW][C]14[/C][C]29[/C][C]11.4891252930761[/C][C]24[/C][/ROW]
[ROW][C]15[/C][C]25.5[/C][C]22.781571499789[/C][C]50[/C][/ROW]
[ROW][C]16[/C][C]33.5[/C][C]16.583123951777[/C][C]37[/C][/ROW]
[ROW][C]17[/C][C]48.5[/C][C]57.7840808527747[/C][C]125[/C][/ROW]
[ROW][C]18[/C][C]74.25[/C][C]46.9565401905492[/C][C]100[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151182&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151182&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
119.259.2870878105033521
2134.555.2237871452752111
398.7582.2166852490012169
475.7554.6343908785178119
554.7550.9795710718192107
6119.7578.0870241034535158
773.552.182372502599120
810232.341923257592557
9135.559.3380147965872130
1075.536.373066958946481
1155.2516.520189667999238
1218.7511.236102527122126
1311.257.2743842809317314
142911.489125293076124
1525.522.78157149978950
1633.516.58312395177737
1748.557.7840808527747125
1874.2546.9565401905492100






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.0929954864587
beta0.468774624156978
S.D.0.0939511445908263
T-STAT4.98955735130821
p-value0.000133654054407979

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.0929954864587 \tabularnewline
beta & 0.468774624156978 \tabularnewline
S.D. & 0.0939511445908263 \tabularnewline
T-STAT & 4.98955735130821 \tabularnewline
p-value & 0.000133654054407979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151182&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.0929954864587[/C][/ROW]
[ROW][C]beta[/C][C]0.468774624156978[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0939511445908263[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.98955735130821[/C][/ROW]
[ROW][C]p-value[/C][C]0.000133654054407979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151182&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151182&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)
alpha8.0929954864587
beta0.468774624156978
S.D.0.0939511445908263
T-STAT4.98955735130821
p-value0.000133654054407979






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.267514759040211
beta0.929402895596044
S.D.0.126167849313063
T-STAT7.36640039959704
p-value1.59015826599004e-06
Lambda0.0705971044039561

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.267514759040211 \tabularnewline
beta & 0.929402895596044 \tabularnewline
S.D. & 0.126167849313063 \tabularnewline
T-STAT & 7.36640039959704 \tabularnewline
p-value & 1.59015826599004e-06 \tabularnewline
Lambda & 0.0705971044039561 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151182&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.267514759040211[/C][/ROW]
[ROW][C]beta[/C][C]0.929402895596044[/C][/ROW]
[ROW][C]S.D.[/C][C]0.126167849313063[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.36640039959704[/C][/ROW]
[ROW][C]p-value[/C][C]1.59015826599004e-06[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0705971044039561[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151182&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151182&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-0.267514759040211
beta0.929402895596044
S.D.0.126167849313063
T-STAT7.36640039959704
p-value1.59015826599004e-06
Lambda0.0705971044039561


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')