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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 computationSun, 20 Mar 2016 17:14:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/20/t14584941154pu3lisf6fv7cd6.htm/, Retrieved Thu, 02 May 2024 10:26:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294370, Retrieved Thu, 02 May 2024 10:26:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

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] [] [2016-03-20 17:14:36] [a1d1814f81d637d5e936c79e282724ec] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
89,65
90,65
89,34
89,15
88,82
88,82
91,97
93,01
93,24
93,2
93,19
92,2
93,39
94,75
94,25
94,37
94,02
92,77
92,64
93,19
92,74
92,52
92,25
91,6
93,73
96,21
96,36
95,69
95,07
95,5
95,22
97,41
98,31
98,54
98,45
98,03
101,45
102,44
102,42
100,98
100,69
100,28
98,06
97,37
97,25
98,93
100,04
100,09
100,79
99,76
99,63
99,26
99,69
99,17
98,79
97,97
98,1
97,91
97,16
96,8
97,46
96,59
96,35
96,12
96,16
95,95
96,06
95,89
95,9
95,82
95,54
95,51

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' @ yule.wessa.net

\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' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294370&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294370&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294370&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' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
191.10333333333331.872637096975734.42
293.20750.9637438833669853.15000000000001
396.54333333333331.581215489502444.81
41001.779300168861095.19
598.75251.181094446227353.99000000000001
696.11250.522461394833061.94999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91.1033333333333 & 1.87263709697573 & 4.42 \tabularnewline
2 & 93.2075 & 0.963743883366985 & 3.15000000000001 \tabularnewline
3 & 96.5433333333333 & 1.58121548950244 & 4.81 \tabularnewline
4 & 100 & 1.77930016886109 & 5.19 \tabularnewline
5 & 98.7525 & 1.18109444622735 & 3.99000000000001 \tabularnewline
6 & 96.1125 & 0.52246139483306 & 1.94999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294370&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]91.1033333333333[/C][C]1.87263709697573[/C][C]4.42[/C][/ROW]
[ROW][C]2[/C][C]93.2075[/C][C]0.963743883366985[/C][C]3.15000000000001[/C][/ROW]
[ROW][C]3[/C][C]96.5433333333333[/C][C]1.58121548950244[/C][C]4.81[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]1.77930016886109[/C][C]5.19[/C][/ROW]
[ROW][C]5[/C][C]98.7525[/C][C]1.18109444622735[/C][C]3.99000000000001[/C][/ROW]
[ROW][C]6[/C][C]96.1125[/C][C]0.52246139483306[/C][C]1.94999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294370&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294370&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
191.10333333333331.872637096975734.42
293.20750.9637438833669853.15000000000001
396.54333333333331.581215489502444.81
41001.779300168861095.19
598.75251.181094446227353.99000000000001
696.11250.522461394833061.94999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.67037329756405
beta-0.00368545538947837
S.D.0.0783405008837668
T-STAT-0.0470440621122202
p-value0.964733211982006

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.67037329756405 \tabularnewline
beta & -0.00368545538947837 \tabularnewline
S.D. & 0.0783405008837668 \tabularnewline
T-STAT & -0.0470440621122202 \tabularnewline
p-value & 0.964733211982006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294370&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.67037329756405[/C][/ROW]
[ROW][C]beta[/C][C]-0.00368545538947837[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0783405008837668[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0470440621122202[/C][/ROW]
[ROW][C]p-value[/C][C]0.964733211982006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294370&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294370&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)
alpha1.67037329756405
beta-0.00368545538947837
S.D.0.0783405008837668
T-STAT-0.0470440621122202
p-value0.964733211982006






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.612447080672272
beta-0.0924982492631224
S.D.6.91765878657459
T-STAT-0.0133713228878299
p-value0.989971881361792
Lambda1.09249824926312

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.612447080672272 \tabularnewline
beta & -0.0924982492631224 \tabularnewline
S.D. & 6.91765878657459 \tabularnewline
T-STAT & -0.0133713228878299 \tabularnewline
p-value & 0.989971881361792 \tabularnewline
Lambda & 1.09249824926312 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294370&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.612447080672272[/C][/ROW]
[ROW][C]beta[/C][C]-0.0924982492631224[/C][/ROW]
[ROW][C]S.D.[/C][C]6.91765878657459[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0133713228878299[/C][/ROW]
[ROW][C]p-value[/C][C]0.989971881361792[/C][/ROW]
[ROW][C]Lambda[/C][C]1.09249824926312[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294370&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294370&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)
alpha0.612447080672272
beta-0.0924982492631224
S.D.6.91765878657459
T-STAT-0.0133713228878299
p-value0.989971881361792
Lambda1.09249824926312


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')