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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 computationTue, 23 Dec 2008 14:10:52 -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/2008/Dec/23/t1230066764lm4jje7gk60yiuh.htm/, Retrieved Fri, 17 May 2024 05:15:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36419, Retrieved Fri, 17 May 2024 05:15:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

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] [Voedingsmiddelen] [2008-12-23 21:10:52] [4feaea4b7a1dc404ed7b3613ea3a9f56] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,29
101,12
102,65
102,71
103,39
102,8
102,07
102,15
101,21
101,27
101,86
101,65
101,94
102,62
102,71
103,39
104,51
104,09
104,29
104,57
105,39
105,15
106,13
105,46
106,47
106,62
106,52
108,04
107,15
107,32
107,76
107,26
107,89
109,08
110,4
111,03
112,05
112,28
112,8
114,17
114,92
114,65
115,49
114,67
114,71
115,15
115,03

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=36419&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=36419&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36419&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
1101.9308333333330.8773043250707693.09999999999999
2104.18751.292025365638984.19
3107.9616666666671.487192799956494.56

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 101.930833333333 & 0.877304325070769 & 3.09999999999999 \tabularnewline
2 & 104.1875 & 1.29202536563898 & 4.19 \tabularnewline
3 & 107.961666666667 & 1.48719279995649 & 4.56 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36419&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]101.930833333333[/C][C]0.877304325070769[/C][C]3.09999999999999[/C][/ROW]
[ROW][C]2[/C][C]104.1875[/C][C]1.29202536563898[/C][C]4.19[/C][/ROW]
[ROW][C]3[/C][C]107.961666666667[/C][C]1.48719279995649[/C][C]4.56[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36419&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36419&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
1101.9308333333330.8773043250707693.09999999999999
2104.18751.292025365638984.19
3107.9616666666671.487192799956494.56






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-8.83672892913767
beta0.0960478517513985
S.D.0.0349718908710205
T-STAT2.7464300430775
p-value0.222300246989410

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -8.83672892913767 \tabularnewline
beta & 0.0960478517513985 \tabularnewline
S.D. & 0.0349718908710205 \tabularnewline
T-STAT & 2.7464300430775 \tabularnewline
p-value & 0.222300246989410 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36419&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.83672892913767[/C][/ROW]
[ROW][C]beta[/C][C]0.0960478517513985[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0349718908710205[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.7464300430775[/C][/ROW]
[ROW][C]p-value[/C][C]0.222300246989410[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36419&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36419&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-8.83672892913767
beta0.0960478517513985
S.D.0.0349718908710205
T-STAT2.7464300430775
p-value0.222300246989410






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-40.1835996385211
beta8.67766039823192
S.D.3.66808050865414
T-STAT2.36572244741048
p-value0.254599644334447
Lambda-7.67766039823192

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -40.1835996385211 \tabularnewline
beta & 8.67766039823192 \tabularnewline
S.D. & 3.66808050865414 \tabularnewline
T-STAT & 2.36572244741048 \tabularnewline
p-value & 0.254599644334447 \tabularnewline
Lambda & -7.67766039823192 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36419&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-40.1835996385211[/C][/ROW]
[ROW][C]beta[/C][C]8.67766039823192[/C][/ROW]
[ROW][C]S.D.[/C][C]3.66808050865414[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.36572244741048[/C][/ROW]
[ROW][C]p-value[/C][C]0.254599644334447[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.67766039823192[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36419&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36419&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-40.1835996385211
beta8.67766039823192
S.D.3.66808050865414
T-STAT2.36572244741048
p-value0.254599644334447
Lambda-7.67766039823192


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
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')