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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 25 Dec 2010 08:32:23 +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/2010/Dec/25/t1293267502iv86lbdlk9xs0px.htm/, Retrieved Mon, 29 Apr 2024 05:29:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115310, Retrieved Mon, 29 Apr 2024 05:29:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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] [sdm plot niet soc] [2010-12-25 08:32:23] [346ac46ef4f6bb745e48fc42fac6253b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104,79
104,82
104,94
105,04
105,17
105,4
105,56
105,66
105,96
105,92
106,03
106,16
106,39
106,41
106,66
106,76
106,97
107,07
107,29
107,39
107,5
107,79
107,77
107,84
108,09
108,28
108,49
108,73
108,84
108,94
109,08
109,38
109,42
109,59
109,83
109,89
110,29
110,33
110,54
110,69
110,77
111,01
111,25
111,09
111,32
111,36
111,31
111,37
111,49
111,49
111,55
111,56
111,66
111,68
111,71
111,76
111,82
111,87
111,94
112,05

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115310&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115310&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115310&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 time8 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1105.4541666666670.4971822115835911.36999999999999
2107.1533333333330.5244795400001691.45000000000000
3109.0466666666670.5907519604604611.80000000000000
4110.9441666666670.4058539444706971.08000000000000
5111.7150.1800757416402140.560000000000002

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 105.454166666667 & 0.497182211583591 & 1.36999999999999 \tabularnewline
2 & 107.153333333333 & 0.524479540000169 & 1.45000000000000 \tabularnewline
3 & 109.046666666667 & 0.590751960460461 & 1.80000000000000 \tabularnewline
4 & 110.944166666667 & 0.405853944470697 & 1.08000000000000 \tabularnewline
5 & 111.715 & 0.180075741640214 & 0.560000000000002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115310&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]105.454166666667[/C][C]0.497182211583591[/C][C]1.36999999999999[/C][/ROW]
[ROW][C]2[/C][C]107.153333333333[/C][C]0.524479540000169[/C][C]1.45000000000000[/C][/ROW]
[ROW][C]3[/C][C]109.046666666667[/C][C]0.590751960460461[/C][C]1.80000000000000[/C][/ROW]
[ROW][C]4[/C][C]110.944166666667[/C][C]0.405853944470697[/C][C]1.08000000000000[/C][/ROW]
[ROW][C]5[/C][C]111.715[/C][C]0.180075741640214[/C][C]0.560000000000002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115310&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115310&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
1105.4541666666670.4971822115835911.36999999999999
2107.1533333333330.5244795400001691.45000000000000
3109.0466666666670.5907519604604611.80000000000000
4110.9441666666670.4058539444706971.08000000000000
5111.7150.1800757416402140.560000000000002






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.96469019188679
beta-0.0415663298613766
S.D.0.0260699615672367
T-STAT-1.59441469655310
p-value0.209103947557439

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.96469019188679 \tabularnewline
beta & -0.0415663298613766 \tabularnewline
S.D. & 0.0260699615672367 \tabularnewline
T-STAT & -1.59441469655310 \tabularnewline
p-value & 0.209103947557439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115310&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.96469019188679[/C][/ROW]
[ROW][C]beta[/C][C]-0.0415663298613766[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0260699615672367[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.59441469655310[/C][/ROW]
[ROW][C]p-value[/C][C]0.209103947557439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115310&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115310&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)
alpha4.96469019188679
beta-0.0415663298613766
S.D.0.0260699615672367
T-STAT-1.59441469655310
p-value0.209103947557439






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha62.2973418908763
beta-13.4747507967633
S.D.8.45637266957064
T-STAT-1.59344335015541
p-value0.209313286986440
Lambda14.4747507967633

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 62.2973418908763 \tabularnewline
beta & -13.4747507967633 \tabularnewline
S.D. & 8.45637266957064 \tabularnewline
T-STAT & -1.59344335015541 \tabularnewline
p-value & 0.209313286986440 \tabularnewline
Lambda & 14.4747507967633 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115310&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]62.2973418908763[/C][/ROW]
[ROW][C]beta[/C][C]-13.4747507967633[/C][/ROW]
[ROW][C]S.D.[/C][C]8.45637266957064[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.59344335015541[/C][/ROW]
[ROW][C]p-value[/C][C]0.209313286986440[/C][/ROW]
[ROW][C]Lambda[/C][C]14.4747507967633[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115310&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115310&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)
alpha62.2973418908763
beta-13.4747507967633
S.D.8.45637266957064
T-STAT-1.59344335015541
p-value0.209313286986440
Lambda14.4747507967633


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')