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Description of Statistical Computation

Author's title

Standard Deviation-Mean Plot-aantal geboortes per maand (2000-2006)-Olivier...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 28 May 2009 05:35:23 -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/t1243510584co13unoxd5f4znh.htm/, Retrieved Mon, 06 May 2024 01:57:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40597, Retrieved Mon, 06 May 2024 01:57:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112

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] [Standard Deviatio...] [2009-05-28 11:35:23] [0a468acfbffe35a0b1f3f2151d8ad87e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9.733
9.259
9.864
9.215
10.103
9.380
9.896
10.117
9.451
9.700
9.081
9.084
9.743
8.587
9.731
9.563
9.998
9.437
10.038
9.918
9.252
9.737
9.035
9.133
9.487
8.700
9.627
8.947
9.283
8.829
9.947
9.628
9.318
9.605
8.640
9.214
9.567
8.547
9.185
9.470
9.123
9.278
10.170
9.434
9.655
9.429
8.739
9.552
9.687
9.019
9.672
9.206
9.069
9.788
10.312
10.105
9.863
9.656
9.295
9.946
9.701
9.049
10.190
9.706
9.765
9.893
9.994
10.433
10.073
10.112
9.266
9.820
10.097
9.115
10.411
9.678
10.408
10.153
10.368
10.581
10.597
10.680
9.738
9.556

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=40597&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=40597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40597&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
19.517750.3290545800724660.649000000000001
29.8740.3444851230459740.737
39.3290.3022438309268420.619
49.4060.5521485307415031.156
59.847750.2783407683637690.601000000000001
69.289250.3114079585795240.702
79.190250.4390621634043790.927000000000001
89.421750.4792461962985891.11800000000000
99.194250.4048097289674080.965
109.192250.4597037995637331.02
119.501250.4635596869156481.047
129.343750.4136160659355480.915999999999999
139.3960.33619736267060.667999999999999
149.81850.5441522458528181.24300000000000
159.690.2901987824463320.651
169.66150.4683335705811971.141
1710.021250.290053299699670.667999999999999
189.817750.3899439062224210.846
199.825250.5606807618125191.296
2010.37750.1759100148750300.427999999999999
2110.142750.578238344744911.124

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9.51775 & 0.329054580072466 & 0.649000000000001 \tabularnewline
2 & 9.874 & 0.344485123045974 & 0.737 \tabularnewline
3 & 9.329 & 0.302243830926842 & 0.619 \tabularnewline
4 & 9.406 & 0.552148530741503 & 1.156 \tabularnewline
5 & 9.84775 & 0.278340768363769 & 0.601000000000001 \tabularnewline
6 & 9.28925 & 0.311407958579524 & 0.702 \tabularnewline
7 & 9.19025 & 0.439062163404379 & 0.927000000000001 \tabularnewline
8 & 9.42175 & 0.479246196298589 & 1.11800000000000 \tabularnewline
9 & 9.19425 & 0.404809728967408 & 0.965 \tabularnewline
10 & 9.19225 & 0.459703799563733 & 1.02 \tabularnewline
11 & 9.50125 & 0.463559686915648 & 1.047 \tabularnewline
12 & 9.34375 & 0.413616065935548 & 0.915999999999999 \tabularnewline
13 & 9.396 & 0.3361973626706 & 0.667999999999999 \tabularnewline
14 & 9.8185 & 0.544152245852818 & 1.24300000000000 \tabularnewline
15 & 9.69 & 0.290198782446332 & 0.651 \tabularnewline
16 & 9.6615 & 0.468333570581197 & 1.141 \tabularnewline
17 & 10.02125 & 0.29005329969967 & 0.667999999999999 \tabularnewline
18 & 9.81775 & 0.389943906222421 & 0.846 \tabularnewline
19 & 9.82525 & 0.560680761812519 & 1.296 \tabularnewline
20 & 10.3775 & 0.175910014875030 & 0.427999999999999 \tabularnewline
21 & 10.14275 & 0.57823834474491 & 1.124 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40597&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]9.51775[/C][C]0.329054580072466[/C][C]0.649000000000001[/C][/ROW]
[ROW][C]2[/C][C]9.874[/C][C]0.344485123045974[/C][C]0.737[/C][/ROW]
[ROW][C]3[/C][C]9.329[/C][C]0.302243830926842[/C][C]0.619[/C][/ROW]
[ROW][C]4[/C][C]9.406[/C][C]0.552148530741503[/C][C]1.156[/C][/ROW]
[ROW][C]5[/C][C]9.84775[/C][C]0.278340768363769[/C][C]0.601000000000001[/C][/ROW]
[ROW][C]6[/C][C]9.28925[/C][C]0.311407958579524[/C][C]0.702[/C][/ROW]
[ROW][C]7[/C][C]9.19025[/C][C]0.439062163404379[/C][C]0.927000000000001[/C][/ROW]
[ROW][C]8[/C][C]9.42175[/C][C]0.479246196298589[/C][C]1.11800000000000[/C][/ROW]
[ROW][C]9[/C][C]9.19425[/C][C]0.404809728967408[/C][C]0.965[/C][/ROW]
[ROW][C]10[/C][C]9.19225[/C][C]0.459703799563733[/C][C]1.02[/C][/ROW]
[ROW][C]11[/C][C]9.50125[/C][C]0.463559686915648[/C][C]1.047[/C][/ROW]
[ROW][C]12[/C][C]9.34375[/C][C]0.413616065935548[/C][C]0.915999999999999[/C][/ROW]
[ROW][C]13[/C][C]9.396[/C][C]0.3361973626706[/C][C]0.667999999999999[/C][/ROW]
[ROW][C]14[/C][C]9.8185[/C][C]0.544152245852818[/C][C]1.24300000000000[/C][/ROW]
[ROW][C]15[/C][C]9.69[/C][C]0.290198782446332[/C][C]0.651[/C][/ROW]
[ROW][C]16[/C][C]9.6615[/C][C]0.468333570581197[/C][C]1.141[/C][/ROW]
[ROW][C]17[/C][C]10.02125[/C][C]0.29005329969967[/C][C]0.667999999999999[/C][/ROW]
[ROW][C]18[/C][C]9.81775[/C][C]0.389943906222421[/C][C]0.846[/C][/ROW]
[ROW][C]19[/C][C]9.82525[/C][C]0.560680761812519[/C][C]1.296[/C][/ROW]
[ROW][C]20[/C][C]10.3775[/C][C]0.175910014875030[/C][C]0.427999999999999[/C][/ROW]
[ROW][C]21[/C][C]10.14275[/C][C]0.57823834474491[/C][C]1.124[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40597&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
19.517750.3290545800724660.649000000000001
29.8740.3444851230459740.737
39.3290.3022438309268420.619
49.4060.5521485307415031.156
59.847750.2783407683637690.601000000000001
69.289250.3114079585795240.702
79.190250.4390621634043790.927000000000001
89.421750.4792461962985891.11800000000000
99.194250.4048097289674080.965
109.192250.4597037995637331.02
119.501250.4635596869156481.047
129.343750.4136160659355480.915999999999999
139.3960.33619736267060.667999999999999
149.81850.5441522458528181.24300000000000
159.690.2901987824463320.651
169.66150.4683335705811971.141
1710.021250.290053299699670.667999999999999
189.817750.3899439062224210.846
199.825250.5606807618125191.296
2010.37750.1759100148750300.427999999999999
2110.142750.578238344744911.124






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.97097185460016
beta-0.0593438806529969
S.D.0.0741311455340578
T-STAT-0.800525612082073
p-value0.433302761533915

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.97097185460016 \tabularnewline
beta & -0.0593438806529969 \tabularnewline
S.D. & 0.0741311455340578 \tabularnewline
T-STAT & -0.800525612082073 \tabularnewline
p-value & 0.433302761533915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40597&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.97097185460016[/C][/ROW]
[ROW][C]beta[/C][C]-0.0593438806529969[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0741311455340578[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.800525612082073[/C][/ROW]
[ROW][C]p-value[/C][C]0.433302761533915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40597&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40597&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)
alpha0.97097185460016
beta-0.0593438806529969
S.D.0.0741311455340578
T-STAT-0.800525612082073
p-value0.433302761533915






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.71979407383035
beta-2.50797419123865
S.D.1.89665749963459
T-STAT-1.32231264301638
p-value0.201762134735638
Lambda3.50797419123865

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.71979407383035 \tabularnewline
beta & -2.50797419123865 \tabularnewline
S.D. & 1.89665749963459 \tabularnewline
T-STAT & -1.32231264301638 \tabularnewline
p-value & 0.201762134735638 \tabularnewline
Lambda & 3.50797419123865 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40597&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.71979407383035[/C][/ROW]
[ROW][C]beta[/C][C]-2.50797419123865[/C][/ROW]
[ROW][C]S.D.[/C][C]1.89665749963459[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.32231264301638[/C][/ROW]
[ROW][C]p-value[/C][C]0.201762134735638[/C][/ROW]
[ROW][C]Lambda[/C][C]3.50797419123865[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40597&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40597&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)
alpha4.71979407383035
beta-2.50797419123865
S.D.1.89665749963459
T-STAT-1.32231264301638
p-value0.201762134735638
Lambda3.50797419123865


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')