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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, 02 Dec 2012 10:49:51 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/02/t1354463460380vj6gmd29m3qe.htm/, Retrieved Thu, 25 Apr 2024 20:20:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195555, Retrieved Thu, 25 Apr 2024 20:20:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

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] [opdracht 8] [2012-12-02 15:49:51] [e25403493d7c2455f6f96b951dac0284] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.42
99.42
99.42
99.42
99.42
109.26
110
110
109.26
100.07
100.07
100.05
100.05
100.05
100.05
100.05
100.05
108.77
111.32
111.6
108.52
103.13
102.87
102.75
102.75
102.75
102.75
102.75
102.75
115.22
115.53
115.4
111.99
107.93
107.43
106.98
106.98
106.98
106.98
106.98
106.98
113.71
118.77
118.54
116.16
110.52
110.06
109.9
109.9
110.72
110.09
110.07
112.45
113.06
119.83
119.84
113.73
110.5
110.12
109.86
110.36
110.36
110.59
112.52
112.1
115.9
122.96
121.26
114.55
111.57
110.65
109.77

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195555&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195555&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195555&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1102.9841666666674.9205181884049810.58
2104.1008333333334.6320277482551911.55
3107.85255.3803601180590112.78
4111.0466666666674.6151338665374111.79
5112.5141666666673.664404846463879.98
6113.5491666666674.4046534449031313.19

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.984166666667 & 4.92051818840498 & 10.58 \tabularnewline
2 & 104.100833333333 & 4.63202774825519 & 11.55 \tabularnewline
3 & 107.8525 & 5.38036011805901 & 12.78 \tabularnewline
4 & 111.046666666667 & 4.61513386653741 & 11.79 \tabularnewline
5 & 112.514166666667 & 3.66440484646387 & 9.98 \tabularnewline
6 & 113.549166666667 & 4.40465344490313 & 13.19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195555&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]102.984166666667[/C][C]4.92051818840498[/C][C]10.58[/C][/ROW]
[ROW][C]2[/C][C]104.100833333333[/C][C]4.63202774825519[/C][C]11.55[/C][/ROW]
[ROW][C]3[/C][C]107.8525[/C][C]5.38036011805901[/C][C]12.78[/C][/ROW]
[ROW][C]4[/C][C]111.046666666667[/C][C]4.61513386653741[/C][C]11.79[/C][/ROW]
[ROW][C]5[/C][C]112.514166666667[/C][C]3.66440484646387[/C][C]9.98[/C][/ROW]
[ROW][C]6[/C][C]113.549166666667[/C][C]4.40465344490313[/C][C]13.19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195555&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195555&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
1102.9841666666674.9205181884049810.58
2104.1008333333334.6320277482551911.55
3107.85255.3803601180590112.78
4111.0466666666674.6151338665374111.79
5112.5141666666673.664404846463879.98
6113.5491666666674.4046534449031313.19






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha12.4903880748839
beta-0.0725794213407459
S.D.0.0531744740339567
T-STAT-1.36492974607323
p-value0.2440085616948

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 12.4903880748839 \tabularnewline
beta & -0.0725794213407459 \tabularnewline
S.D. & 0.0531744740339567 \tabularnewline
T-STAT & -1.36492974607323 \tabularnewline
p-value & 0.2440085616948 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195555&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.4903880748839[/C][/ROW]
[ROW][C]beta[/C][C]-0.0725794213407459[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0531744740339567[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.36492974607323[/C][/ROW]
[ROW][C]p-value[/C][C]0.2440085616948[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195555&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195555&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)
alpha12.4903880748839
beta-0.0725794213407459
S.D.0.0531744740339567
T-STAT-1.36492974607323
p-value0.2440085616948






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha9.8220116594689
beta-1.77104099312104
S.D.1.29372565653955
T-STAT-1.36894633276286
p-value0.242853121975017
Lambda2.77104099312104

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.8220116594689 \tabularnewline
beta & -1.77104099312104 \tabularnewline
S.D. & 1.29372565653955 \tabularnewline
T-STAT & -1.36894633276286 \tabularnewline
p-value & 0.242853121975017 \tabularnewline
Lambda & 2.77104099312104 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195555&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.8220116594689[/C][/ROW]
[ROW][C]beta[/C][C]-1.77104099312104[/C][/ROW]
[ROW][C]S.D.[/C][C]1.29372565653955[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.36894633276286[/C][/ROW]
[ROW][C]p-value[/C][C]0.242853121975017[/C][/ROW]
[ROW][C]Lambda[/C][C]2.77104099312104[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195555&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195555&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)
alpha9.8220116594689
beta-1.77104099312104
S.D.1.29372565653955
T-STAT-1.36894633276286
p-value0.242853121975017
Lambda2.77104099312104


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')