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Description of Statistical Computation

Author's title

Agneta Peers - Standard Deviation Mean Plot aantal werklozen jonger dan 25j...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 28 May 2009 12:46:07 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/28/t1243536452rza4nexsmi9iuxr.htm/, Retrieved Sun, 05 May 2024 21:25:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40692, Retrieved Sun, 05 May 2024 21:25:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

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] [Agneta Peers - St...] [2009-05-28 18:46:07] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   P     [Standard Deviation-Mean Plot] [Agneta Peers- Sta...] [2009-06-07 15:10:43] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
122.860
117.702
113.537
108.366
111.078
150.739
159.129
157.928
147.768
137.507
136.919
136.151
133.001
125.554
119.647
114.158
116.193
152.803
161.761
160.942
149.470
139.208
134.588
130.322
126.611
122.401
117.352
112.135
112.879
148.729
157.230
157.221
146.681
136.524
132.111
125.326
122.716
116.615
113.719
110.737
112.093
143.565
149.946
149.147
134.339
122.683
115.614
116.566
111.272
104.609
101.802
94.542
93.051
124.129
130.374
123.946
114.971
105.531
104.919
104.782
101.281
94.545
93.248
84.031
87.486
115.867
120.327
117.008
108.811
104.519
106.758
109.337

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40692&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40692&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40692&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1115.616256.156613591631914.494
2144.718522.730911852951848.051
3139.586255.482684219431211.617
4123.098.081544613088118.843
5147.9247521.537501346488645.568
6138.3978.2256338357600119.148
7119.624756.2657003000462714.476
8144.0147521.140064275761644.351
9135.16058.955406058167721.355
10115.946755.1112186658369411.979
11138.6877517.955615637361737.853
12122.30058.6152105990896518.725
13103.056256.9276060499521316.73
14117.87516.816911468320637.323
15107.550754.9575391997105510.189
1693.276257.0983846695333917.25
17110.17215.241856208043332.841
18107.356252.194505164420144.818

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 115.61625 & 6.1566135916319 & 14.494 \tabularnewline
2 & 144.7185 & 22.7309118529518 & 48.051 \tabularnewline
3 & 139.58625 & 5.4826842194312 & 11.617 \tabularnewline
4 & 123.09 & 8.0815446130881 & 18.843 \tabularnewline
5 & 147.92475 & 21.5375013464886 & 45.568 \tabularnewline
6 & 138.397 & 8.22563383576001 & 19.148 \tabularnewline
7 & 119.62475 & 6.26570030004627 & 14.476 \tabularnewline
8 & 144.01475 & 21.1400642757616 & 44.351 \tabularnewline
9 & 135.1605 & 8.9554060581677 & 21.355 \tabularnewline
10 & 115.94675 & 5.11121866583694 & 11.979 \tabularnewline
11 & 138.68775 & 17.9556156373617 & 37.853 \tabularnewline
12 & 122.3005 & 8.61521059908965 & 18.725 \tabularnewline
13 & 103.05625 & 6.92760604995213 & 16.73 \tabularnewline
14 & 117.875 & 16.8169114683206 & 37.323 \tabularnewline
15 & 107.55075 & 4.95753919971055 & 10.189 \tabularnewline
16 & 93.27625 & 7.09838466953339 & 17.25 \tabularnewline
17 & 110.172 & 15.2418562080433 & 32.841 \tabularnewline
18 & 107.35625 & 2.19450516442014 & 4.818 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40692&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]115.61625[/C][C]6.1566135916319[/C][C]14.494[/C][/ROW]
[ROW][C]2[/C][C]144.7185[/C][C]22.7309118529518[/C][C]48.051[/C][/ROW]
[ROW][C]3[/C][C]139.58625[/C][C]5.4826842194312[/C][C]11.617[/C][/ROW]
[ROW][C]4[/C][C]123.09[/C][C]8.0815446130881[/C][C]18.843[/C][/ROW]
[ROW][C]5[/C][C]147.92475[/C][C]21.5375013464886[/C][C]45.568[/C][/ROW]
[ROW][C]6[/C][C]138.397[/C][C]8.22563383576001[/C][C]19.148[/C][/ROW]
[ROW][C]7[/C][C]119.62475[/C][C]6.26570030004627[/C][C]14.476[/C][/ROW]
[ROW][C]8[/C][C]144.01475[/C][C]21.1400642757616[/C][C]44.351[/C][/ROW]
[ROW][C]9[/C][C]135.1605[/C][C]8.9554060581677[/C][C]21.355[/C][/ROW]
[ROW][C]10[/C][C]115.94675[/C][C]5.11121866583694[/C][C]11.979[/C][/ROW]
[ROW][C]11[/C][C]138.68775[/C][C]17.9556156373617[/C][C]37.853[/C][/ROW]
[ROW][C]12[/C][C]122.3005[/C][C]8.61521059908965[/C][C]18.725[/C][/ROW]
[ROW][C]13[/C][C]103.05625[/C][C]6.92760604995213[/C][C]16.73[/C][/ROW]
[ROW][C]14[/C][C]117.875[/C][C]16.8169114683206[/C][C]37.323[/C][/ROW]
[ROW][C]15[/C][C]107.55075[/C][C]4.95753919971055[/C][C]10.189[/C][/ROW]
[ROW][C]16[/C][C]93.27625[/C][C]7.09838466953339[/C][C]17.25[/C][/ROW]
[ROW][C]17[/C][C]110.172[/C][C]15.2418562080433[/C][C]32.841[/C][/ROW]
[ROW][C]18[/C][C]107.35625[/C][C]2.19450516442014[/C][C]4.818[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40692&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40692&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
1115.616256.156613591631914.494
2144.718522.730911852951848.051
3139.586255.482684219431211.617
4123.098.081544613088118.843
5147.9247521.537501346488645.568
6138.3978.2256338357600119.148
7119.624756.2657003000462714.476
8144.0147521.140064275761644.351
9135.16058.955406058167721.355
10115.946755.1112186658369411.979
11138.6877517.955615637361737.853
12122.30058.6152105990896518.725
13103.056256.9276060499521316.73
14117.87516.816911468320637.323
15107.550754.9575391997105510.189
1693.276257.0983846695333917.25
17110.17215.241856208043332.841
18107.356252.194505164420144.818






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-20.0146578021134
beta0.248952588461859
S.D.0.079367750572648
T-STAT3.13669704213154
p-value0.00637052842558915

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -20.0146578021134 \tabularnewline
beta & 0.248952588461859 \tabularnewline
S.D. & 0.079367750572648 \tabularnewline
T-STAT & 3.13669704213154 \tabularnewline
p-value & 0.00637052842558915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40692&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-20.0146578021134[/C][/ROW]
[ROW][C]beta[/C][C]0.248952588461859[/C][/ROW]
[ROW][C]S.D.[/C][C]0.079367750572648[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.13669704213154[/C][/ROW]
[ROW][C]p-value[/C][C]0.00637052842558915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40692&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40692&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-20.0146578021134
beta0.248952588461859
S.D.0.079367750572648
T-STAT3.13669704213154
p-value0.00637052842558915






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-10.7730008585799
beta2.69666430956134
S.D.0.972675962211678
T-STAT2.77241796274028
p-value0.0135924729290102
Lambda-1.69666430956134

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.7730008585799 \tabularnewline
beta & 2.69666430956134 \tabularnewline
S.D. & 0.972675962211678 \tabularnewline
T-STAT & 2.77241796274028 \tabularnewline
p-value & 0.0135924729290102 \tabularnewline
Lambda & -1.69666430956134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40692&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.7730008585799[/C][/ROW]
[ROW][C]beta[/C][C]2.69666430956134[/C][/ROW]
[ROW][C]S.D.[/C][C]0.972675962211678[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.77241796274028[/C][/ROW]
[ROW][C]p-value[/C][C]0.0135924729290102[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.69666430956134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40692&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40692&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-10.7730008585799
beta2.69666430956134
S.D.0.972675962211678
T-STAT2.77241796274028
p-value0.0135924729290102
Lambda-1.69666430956134


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')