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Description of Statistical Computation

Author's title

Standard Deviation- Mean Plot-Indexcijfer van de consumptieprijzen van hote...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 30 Nov 2012 06:05:25 -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/Nov/30/t1354273629gmb3hk985hbawh7.htm/, Retrieved Fri, 03 May 2024 22:29:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194928, Retrieved Fri, 03 May 2024 22:29:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54

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] [Standard Deviatio...] [2012-11-30 11:05:25] [6f8d6446e5f32bdf63bde1c9ab07ce03] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,51
104,35
104,51
105,25
105,2
105,87
107,63
107,77
106,58
106,32
106,3
106,38
106,42
107,35
107,58
108,2
108,29
108,76
110,69
110,56
108,81
108,81
108,81
109,74
109,57
110,44
111,2
111,44
111,83
112,87
115,07
115,35
113,81
114,66
114,51
115,11
114,54
115,39
115,65
116,46
116,18
116,63
118,84
118,77
117,83
117,66
117,36
118
117,34
118,04
118,17
118,82
119
118,89
121,4
121,01
120,21
120,39
120,09
120,76
120,33
120,84
121,49
122,29
121,91
122,46
124,94
124,6
123,09
123,25
123,01
123,82

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194928&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194928&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194928&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1105.8058333333331.292379470964194.25999999999999
2108.6683333333331.251274501773244.27
3112.9883333333332.029947752723675.78
4116.94251.358475917409584.3
5119.511.306327259568184.06
6122.6691666666671.408148096119894.61

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 105.805833333333 & 1.29237947096419 & 4.25999999999999 \tabularnewline
2 & 108.668333333333 & 1.25127450177324 & 4.27 \tabularnewline
3 & 112.988333333333 & 2.02994775272367 & 5.78 \tabularnewline
4 & 116.9425 & 1.35847591740958 & 4.3 \tabularnewline
5 & 119.51 & 1.30632725956818 & 4.06 \tabularnewline
6 & 122.669166666667 & 1.40814809611989 & 4.61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194928&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]105.805833333333[/C][C]1.29237947096419[/C][C]4.25999999999999[/C][/ROW]
[ROW][C]2[/C][C]108.668333333333[/C][C]1.25127450177324[/C][C]4.27[/C][/ROW]
[ROW][C]3[/C][C]112.988333333333[/C][C]2.02994775272367[/C][C]5.78[/C][/ROW]
[ROW][C]4[/C][C]116.9425[/C][C]1.35847591740958[/C][C]4.3[/C][/ROW]
[ROW][C]5[/C][C]119.51[/C][C]1.30632725956818[/C][C]4.06[/C][/ROW]
[ROW][C]6[/C][C]122.669166666667[/C][C]1.40814809611989[/C][C]4.61[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194928&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194928&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
1105.8058333333331.292379470964194.25999999999999
2108.6683333333331.251274501773244.27
3112.9883333333332.029947752723675.78
4116.94251.358475917409584.3
5119.511.306327259568184.06
6122.6691666666671.408148096119894.61






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.24261242341199
beta0.00173449740891706
S.D.0.0226528705660242
T-STAT0.0765685480726021
p-value0.942643622058373

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.24261242341199 \tabularnewline
beta & 0.00173449740891706 \tabularnewline
S.D. & 0.0226528705660242 \tabularnewline
T-STAT & 0.0765685480726021 \tabularnewline
p-value & 0.942643622058373 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194928&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.24261242341199[/C][/ROW]
[ROW][C]beta[/C][C]0.00173449740891706[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0226528705660242[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0765685480726021[/C][/ROW]
[ROW][C]p-value[/C][C]0.942643622058373[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194928&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194928&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)
alpha1.24261242341199
beta0.00173449740891706
S.D.0.0226528705660242
T-STAT0.0765685480726021
p-value0.942643622058373






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.885898597992567
beta0.260972472908024
S.D.1.57598310658455
T-STAT0.165593445651584
p-value0.876509341197613
Lambda0.739027527091976

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.885898597992567 \tabularnewline
beta & 0.260972472908024 \tabularnewline
S.D. & 1.57598310658455 \tabularnewline
T-STAT & 0.165593445651584 \tabularnewline
p-value & 0.876509341197613 \tabularnewline
Lambda & 0.739027527091976 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194928&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.885898597992567[/C][/ROW]
[ROW][C]beta[/C][C]0.260972472908024[/C][/ROW]
[ROW][C]S.D.[/C][C]1.57598310658455[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.165593445651584[/C][/ROW]
[ROW][C]p-value[/C][C]0.876509341197613[/C][/ROW]
[ROW][C]Lambda[/C][C]0.739027527091976[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194928&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194928&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-0.885898597992567
beta0.260972472908024
S.D.1.57598310658455
T-STAT0.165593445651584
p-value0.876509341197613
Lambda0.739027527091976


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')