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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, 01 Jun 2008 12:20:05 -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/2008/Jun/01/t1212344472bfd9ec6ojj2dywy.htm/, Retrieved Sat, 18 May 2024 16:51:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13726, Retrieved Sat, 18 May 2024 16:51:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact203

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] [opgave 8, oef 3, ...] [2008-06-01 18:20:05] [2b08e9b5345c911f5a04c663d4ad43d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
78
69
78
74
81
80
76
71
72
69
70
68
62
57
49
57
57
58
53
55
62
54
62
68
73
74
79
77
76
83
77
84
78
74
75
79
79
82
88
81
69
62
62
68
57
67
72
75
81
80
79
81
83
84
90
84
90
92
93
85
93
94
94
102
96
96
92
90
84
86
70
67

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13726&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13726&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13726&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
173.83333333333334.6286328893359513
257.83333333333335.060243137049919
377.41666666666673.4498572653829011
471.83333333333339.3889038311996331
585.16666666666674.8772819057215514
688.666666666666710.534215536512335

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 73.8333333333333 & 4.62863288933595 & 13 \tabularnewline
2 & 57.8333333333333 & 5.0602431370499 & 19 \tabularnewline
3 & 77.4166666666667 & 3.44985726538290 & 11 \tabularnewline
4 & 71.8333333333333 & 9.38890383119963 & 31 \tabularnewline
5 & 85.1666666666667 & 4.87728190572155 & 14 \tabularnewline
6 & 88.6666666666667 & 10.5342155365123 & 35 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13726&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]73.8333333333333[/C][C]4.62863288933595[/C][C]13[/C][/ROW]
[ROW][C]2[/C][C]57.8333333333333[/C][C]5.0602431370499[/C][C]19[/C][/ROW]
[ROW][C]3[/C][C]77.4166666666667[/C][C]3.44985726538290[/C][C]11[/C][/ROW]
[ROW][C]4[/C][C]71.8333333333333[/C][C]9.38890383119963[/C][C]31[/C][/ROW]
[ROW][C]5[/C][C]85.1666666666667[/C][C]4.87728190572155[/C][C]14[/C][/ROW]
[ROW][C]6[/C][C]88.6666666666667[/C][C]10.5342155365123[/C][C]35[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13726&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13726&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
173.83333333333334.6286328893359513
257.83333333333335.060243137049919
377.41666666666673.4498572653829011
471.83333333333339.3889038311996331
585.16666666666674.8772819057215514
688.666666666666710.534215536512335






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.00750773282573888
beta0.0833294956970814
S.D.0.125660485799460
T-STAT0.663132051153026
p-value0.543509525607268

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.00750773282573888 \tabularnewline
beta & 0.0833294956970814 \tabularnewline
S.D. & 0.125660485799460 \tabularnewline
T-STAT & 0.663132051153026 \tabularnewline
p-value & 0.543509525607268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13726&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.00750773282573888[/C][/ROW]
[ROW][C]beta[/C][C]0.0833294956970814[/C][/ROW]
[ROW][C]S.D.[/C][C]0.125660485799460[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.663132051153026[/C][/ROW]
[ROW][C]p-value[/C][C]0.543509525607268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13726&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13726&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)
alpha0.00750773282573888
beta0.0833294956970814
S.D.0.125660485799460
T-STAT0.663132051153026
p-value0.543509525607268






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.23110057067655
beta0.693001937105017
S.D.1.40151763713329
T-STAT0.494465370070195
p-value0.646902957688247
Lambda0.306998062894983

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.23110057067655 \tabularnewline
beta & 0.693001937105017 \tabularnewline
S.D. & 1.40151763713329 \tabularnewline
T-STAT & 0.494465370070195 \tabularnewline
p-value & 0.646902957688247 \tabularnewline
Lambda & 0.306998062894983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13726&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.23110057067655[/C][/ROW]
[ROW][C]beta[/C][C]0.693001937105017[/C][/ROW]
[ROW][C]S.D.[/C][C]1.40151763713329[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.494465370070195[/C][/ROW]
[ROW][C]p-value[/C][C]0.646902957688247[/C][/ROW]
[ROW][C]Lambda[/C][C]0.306998062894983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13726&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13726&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-1.23110057067655
beta0.693001937105017
S.D.1.40151763713329
T-STAT0.494465370070195
p-value0.646902957688247
Lambda0.306998062894983


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')