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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 26 Nov 2009 03:34:25 -0700
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/Nov/26/t1259231743fnjjhqxd141673p.htm/, Retrieved Sun, 28 Apr 2024 23:42:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59799, Retrieved Sun, 28 Apr 2024 23:42:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D          [Standard Deviation-Mean Plot] [] [2009-11-26 10:34:25] [faa1ded5041cd5a0e2be04844f08502a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
24
22
25
24
29
26
26
21
23
22
21
16
19
16
25
27
23
22
23
20
24
23
20
21
22
17
21
19
23
22
15
23
21
18
18
18
18
10
13
10
9
9
6
11
9
10
9
16
10
7
7
14
11
10
6
8
13
12
15
16
16

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=59799&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=59799&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59799&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
123.253.27871926215113
221.91666666666672.9374798516394811
319.752.598076211353328
410.83333333333333.325748947320912
510.753.3337120996925310

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 23.25 & 3.278719262151 & 13 \tabularnewline
2 & 21.9166666666667 & 2.93747985163948 & 11 \tabularnewline
3 & 19.75 & 2.59807621135332 & 8 \tabularnewline
4 & 10.8333333333333 & 3.3257489473209 & 12 \tabularnewline
5 & 10.75 & 3.33371209969253 & 10 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59799&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]23.25[/C][C]3.278719262151[/C][C]13[/C][/ROW]
[ROW][C]2[/C][C]21.9166666666667[/C][C]2.93747985163948[/C][C]11[/C][/ROW]
[ROW][C]3[/C][C]19.75[/C][C]2.59807621135332[/C][C]8[/C][/ROW]
[ROW][C]4[/C][C]10.8333333333333[/C][C]3.3257489473209[/C][C]12[/C][/ROW]
[ROW][C]5[/C][C]10.75[/C][C]3.33371209969253[/C][C]10[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59799&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59799&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
123.253.27871926215113
221.91666666666672.9374798516394811
319.752.598076211353328
410.83333333333333.325748947320912
510.753.3337120996925310






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.55321627290441
beta-0.0265010981776283
S.D.0.0265665646076646
T-STAT-0.997535758536975
p-value0.392022430589717

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.55321627290441 \tabularnewline
beta & -0.0265010981776283 \tabularnewline
S.D. & 0.0265665646076646 \tabularnewline
T-STAT & -0.997535758536975 \tabularnewline
p-value & 0.392022430589717 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59799&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.55321627290441[/C][/ROW]
[ROW][C]beta[/C][C]-0.0265010981776283[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0265665646076646[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.997535758536975[/C][/ROW]
[ROW][C]p-value[/C][C]0.392022430589717[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59799&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59799&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)
alpha3.55321627290441
beta-0.0265010981776283
S.D.0.0265665646076646
T-STAT-0.997535758536975
p-value0.392022430589717






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.54525108695220
beta-0.150326459739981
S.D.0.138337418312346
T-STAT-1.08666521013545
p-value0.356695512011962
Lambda1.15032645973998

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.54525108695220 \tabularnewline
beta & -0.150326459739981 \tabularnewline
S.D. & 0.138337418312346 \tabularnewline
T-STAT & -1.08666521013545 \tabularnewline
p-value & 0.356695512011962 \tabularnewline
Lambda & 1.15032645973998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59799&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.54525108695220[/C][/ROW]
[ROW][C]beta[/C][C]-0.150326459739981[/C][/ROW]
[ROW][C]S.D.[/C][C]0.138337418312346[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.08666521013545[/C][/ROW]
[ROW][C]p-value[/C][C]0.356695512011962[/C][/ROW]
[ROW][C]Lambda[/C][C]1.15032645973998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59799&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59799&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)
alpha1.54525108695220
beta-0.150326459739981
S.D.0.138337418312346
T-STAT-1.08666521013545
p-value0.356695512011962
Lambda1.15032645973998


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')