FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Renske van der Eijk - Maandelijkse verkoop rode wijn - Opgave 8 standard de...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 20 May 2009 13:24:34 -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/20/t1242847513pyiv6kwc4zwxqw2.htm/, Retrieved Tue, 30 Apr 2024 00:35:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40234, Retrieved Tue, 30 Apr 2024 00:35:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

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] [Renske van der Ei...] [2009-05-20 19:24:34] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
464
675
703
887
1139
1077
1318
1260
1120
963
996
960
530
883
894
1045
1199
1287
1565
1577
1076
918
1008
1063
544
635
804
980
1018
1064
1404
1286
1104
999
996
1015
615
722
832
977
1270
1437
1520
1708
1151
934
1159
1209
699
830
996
1124
1458
1270
1753
2258
1208
1241
1265
1828
809
997
1164
1205
1538
1513
1378
2083
1357
1536
1526
1376

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=40234&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=40234&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40234&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
1963.5250.321792898661854
21087.08333333333293.4907334245171047
3987.416666666667240.938867513707860
41127.83333333333328.8848467537571093
51327.5440.7853528336981559
61373.5320.8747985798141274

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 963.5 & 250.321792898661 & 854 \tabularnewline
2 & 1087.08333333333 & 293.490733424517 & 1047 \tabularnewline
3 & 987.416666666667 & 240.938867513707 & 860 \tabularnewline
4 & 1127.83333333333 & 328.884846753757 & 1093 \tabularnewline
5 & 1327.5 & 440.785352833698 & 1559 \tabularnewline
6 & 1373.5 & 320.874798579814 & 1274 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40234&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]963.5[/C][C]250.321792898661[/C][C]854[/C][/ROW]
[ROW][C]2[/C][C]1087.08333333333[/C][C]293.490733424517[/C][C]1047[/C][/ROW]
[ROW][C]3[/C][C]987.416666666667[/C][C]240.938867513707[/C][C]860[/C][/ROW]
[ROW][C]4[/C][C]1127.83333333333[/C][C]328.884846753757[/C][C]1093[/C][/ROW]
[ROW][C]5[/C][C]1327.5[/C][C]440.785352833698[/C][C]1559[/C][/ROW]
[ROW][C]6[/C][C]1373.5[/C][C]320.874798579814[/C][C]1274[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40234&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40234&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
1963.5250.321792898661854
21087.08333333333293.4907334245171047
3987.416666666667240.938867513707860
41127.83333333333328.8848467537571093
51327.5440.7853528336981559
61373.5320.8747985798141274






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-66.8191981337622
beta0.331479077809771
S.D.0.130427334125793
T-STAT2.54148472811742
p-value0.0638800967098916

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -66.8191981337622 \tabularnewline
beta & 0.331479077809771 \tabularnewline
S.D. & 0.130427334125793 \tabularnewline
T-STAT & 2.54148472811742 \tabularnewline
p-value & 0.0638800967098916 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40234&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-66.8191981337622[/C][/ROW]
[ROW][C]beta[/C][C]0.331479077809771[/C][/ROW]
[ROW][C]S.D.[/C][C]0.130427334125793[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.54148472811742[/C][/ROW]
[ROW][C]p-value[/C][C]0.0638800967098916[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40234&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40234&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-66.8191981337622
beta0.331479077809771
S.D.0.130427334125793
T-STAT2.54148472811742
p-value0.0638800967098916






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.90367080761789
beta1.22666059727857
S.D.0.416794535345625
T-STAT2.94308224617524
p-value0.0422592281258662
Lambda-0.226660597278568

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.90367080761789 \tabularnewline
beta & 1.22666059727857 \tabularnewline
S.D. & 0.416794535345625 \tabularnewline
T-STAT & 2.94308224617524 \tabularnewline
p-value & 0.0422592281258662 \tabularnewline
Lambda & -0.226660597278568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40234&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.90367080761789[/C][/ROW]
[ROW][C]beta[/C][C]1.22666059727857[/C][/ROW]
[ROW][C]S.D.[/C][C]0.416794535345625[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.94308224617524[/C][/ROW]
[ROW][C]p-value[/C][C]0.0422592281258662[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.226660597278568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40234&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40234&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-2.90367080761789
beta1.22666059727857
S.D.0.416794535345625
T-STAT2.94308224617524
p-value0.0422592281258662
Lambda-0.226660597278568


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')