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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 computationWed, 13 Apr 2016 15:48:24 +0100
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/Apr/13/t1460558924nashsbhebsfurh8.htm/, Retrieved Sun, 05 May 2024 23:23:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294554, Retrieved Sun, 05 May 2024 23:23:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180

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] [oefening 8.2 stap 3] [2016-04-13 14:48:24] [76c30f62b7052b57088120e90a652e05] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96.86
96.89
96.90
96.94
96.88
96.89
96.89
96.95
97.03
97.29
97.37
97.41
97.41
97.41
97.46
97.51
97.56
97.61
97.66
97.71
97.76
97.81
97.86
97.91
97.96
98.01
98.06
98.12
98.17
98.22
98.27
98.32
98.37
98.42
98.47
98.52
98.57
98.62
98.67
98.72
98.77
98.82
98.87
98.92
98.97
99.02
99.07
99.12
99.18
99.23
99.28
99.33
99.38
99.43
99.48
99.53
99.58
99.63
99.68
99.73
99.78
99.83
99.88
99.93
99.98
100.03
100.08
100.13
100.19
100.24
100.29
100.34
100.39
100.44
100.49
100.54
100.59
100.64
100.69
100.74
100.79
100.84
100.89
100.94
100.99
101.04
101.09
101.14
101.20
101.25
101.30
101.35
101.40
101.45
101.50
101.55
101.60
101.65
101.70
101.75
101.80
101.85
101.90
101.95
102.00
102.05
102.10
102.15

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294554&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294554&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'Sir Maurice George Kendall' @ kendall.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
197.0250.2064637322322570.549999999999997
297.63916666666670.1738054467884520.5
398.24250.1837055450244410.560000000000002
498.8450.18027756377320.550000000000011
599.4550.1802775637731990.549999999999997
6100.0583333333330.1843333607320930.560000000000002
7100.6650.18027756377320.549999999999997
8101.2716666666670.1843333607320920.560000000000002
9101.8750.18027756377320.550000000000011

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 97.025 & 0.206463732232257 & 0.549999999999997 \tabularnewline
2 & 97.6391666666667 & 0.173805446788452 & 0.5 \tabularnewline
3 & 98.2425 & 0.183705545024441 & 0.560000000000002 \tabularnewline
4 & 98.845 & 0.1802775637732 & 0.550000000000011 \tabularnewline
5 & 99.455 & 0.180277563773199 & 0.549999999999997 \tabularnewline
6 & 100.058333333333 & 0.184333360732093 & 0.560000000000002 \tabularnewline
7 & 100.665 & 0.1802775637732 & 0.549999999999997 \tabularnewline
8 & 101.271666666667 & 0.184333360732092 & 0.560000000000002 \tabularnewline
9 & 101.875 & 0.1802775637732 & 0.550000000000011 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294554&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]97.025[/C][C]0.206463732232257[/C][C]0.549999999999997[/C][/ROW]
[ROW][C]2[/C][C]97.6391666666667[/C][C]0.173805446788452[/C][C]0.5[/C][/ROW]
[ROW][C]3[/C][C]98.2425[/C][C]0.183705545024441[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]4[/C][C]98.845[/C][C]0.1802775637732[/C][C]0.550000000000011[/C][/ROW]
[ROW][C]5[/C][C]99.455[/C][C]0.180277563773199[/C][C]0.549999999999997[/C][/ROW]
[ROW][C]6[/C][C]100.058333333333[/C][C]0.184333360732093[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]7[/C][C]100.665[/C][C]0.1802775637732[/C][C]0.549999999999997[/C][/ROW]
[ROW][C]8[/C][C]101.271666666667[/C][C]0.184333360732092[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]9[/C][C]101.875[/C][C]0.1802775637732[/C][C]0.550000000000011[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294554&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294554&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
197.0250.2064637322322570.549999999999997
297.63916666666670.1738054467884520.5
398.24250.1837055450244410.560000000000002
498.8450.18027756377320.550000000000011
599.4550.1802775637731990.549999999999997
6100.0583333333330.1843333607320930.560000000000002
7100.6650.18027756377320.549999999999997
8101.2716666666670.1843333607320920.560000000000002
9101.8750.18027756377320.550000000000011






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.392134621745011
beta-0.00209530643010428
S.D.0.00191754763851763
T-STAT-1.09270110844498
p-value0.310697892342017

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.392134621745011 \tabularnewline
beta & -0.00209530643010428 \tabularnewline
S.D. & 0.00191754763851763 \tabularnewline
T-STAT & -1.09270110844498 \tabularnewline
p-value & 0.310697892342017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294554&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.392134621745011[/C][/ROW]
[ROW][C]beta[/C][C]-0.00209530643010428[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00191754763851763[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.09270110844498[/C][/ROW]
[ROW][C]p-value[/C][C]0.310697892342017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294554&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294554&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)
alpha0.392134621745011
beta-0.00209530643010428
S.D.0.00191754763851763
T-STAT-1.09270110844498
p-value0.310697892342017






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.15946497522631
beta-1.05546555906361
S.D.1.00216475993403
T-STAT-1.05318566493307
p-value0.327246586734973
Lambda2.05546555906361

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.15946497522631 \tabularnewline
beta & -1.05546555906361 \tabularnewline
S.D. & 1.00216475993403 \tabularnewline
T-STAT & -1.05318566493307 \tabularnewline
p-value & 0.327246586734973 \tabularnewline
Lambda & 2.05546555906361 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294554&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.15946497522631[/C][/ROW]
[ROW][C]beta[/C][C]-1.05546555906361[/C][/ROW]
[ROW][C]S.D.[/C][C]1.00216475993403[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.05318566493307[/C][/ROW]
[ROW][C]p-value[/C][C]0.327246586734973[/C][/ROW]
[ROW][C]Lambda[/C][C]2.05546555906361[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294554&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294554&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)
alpha3.15946497522631
beta-1.05546555906361
S.D.1.00216475993403
T-STAT-1.05318566493307
p-value0.327246586734973
Lambda2.05546555906361


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')