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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 computationThu, 19 Nov 2015 12:03:39 +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/2015/Nov/19/t144793473307etj0gd1xnnb9g.htm/, Retrieved Tue, 14 May 2024 02:19:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283599, Retrieved Tue, 14 May 2024 02:19:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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] [] [2015-11-19 12:03:39] [88f551c1d3f4ff2d65b8ab6790c1e3d2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
94.94
95.11
95.53
95.89
95.99
95.42
95.42
95.45
95.99
95.99
95.97
95.97
95.97
96.22
95.8
96.02
96.04
96.15
96.15
95.99
96.08
96.29
96.3
96.44
96.44
96.83
96.7
97.06
97.64
97.61
97.61
97.61
97.55
97.58
97.79
97.79
97.79
97.79
98
98.37
98.68
98.89
98.89
98.89
98.88
98.97
99.05
99.05
99
99.03
99.2
100.3
100.79
100.75
100.75
100.17
99.98
99.93
100.04
100.04
100.49
100.71
100.7
101.27
101.07
101.17
100.71
100.59
100.52
100.65
100.62
100.62

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'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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283599&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283599&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283599&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
195.63916666666670.3770328737375391.05
296.12083333333330.1745882602183230.640000000000001
397.35083333333330.464375599024861.35000000000001
498.60416666666670.4865361489575281.25999999999999
599.99833333333330.6365651196186861.79000000000001
6100.760.2599999999999990.780000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 95.6391666666667 & 0.377032873737539 & 1.05 \tabularnewline
2 & 96.1208333333333 & 0.174588260218323 & 0.640000000000001 \tabularnewline
3 & 97.3508333333333 & 0.46437559902486 & 1.35000000000001 \tabularnewline
4 & 98.6041666666667 & 0.486536148957528 & 1.25999999999999 \tabularnewline
5 & 99.9983333333333 & 0.636565119618686 & 1.79000000000001 \tabularnewline
6 & 100.76 & 0.259999999999999 & 0.780000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283599&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]95.6391666666667[/C][C]0.377032873737539[/C][C]1.05[/C][/ROW]
[ROW][C]2[/C][C]96.1208333333333[/C][C]0.174588260218323[/C][C]0.640000000000001[/C][/ROW]
[ROW][C]3[/C][C]97.3508333333333[/C][C]0.46437559902486[/C][C]1.35000000000001[/C][/ROW]
[ROW][C]4[/C][C]98.6041666666667[/C][C]0.486536148957528[/C][C]1.25999999999999[/C][/ROW]
[ROW][C]5[/C][C]99.9983333333333[/C][C]0.636565119618686[/C][C]1.79000000000001[/C][/ROW]
[ROW][C]6[/C][C]100.76[/C][C]0.259999999999999[/C][C]0.780000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283599&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283599&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
195.63916666666670.3770328737375391.05
296.12083333333330.1745882602183230.640000000000001
397.35083333333330.464375599024861.35000000000001
498.60416666666670.4865361489575281.25999999999999
599.99833333333330.6365651196186861.79000000000001
6100.760.2599999999999990.780000000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.22614773274332
beta0.0267743387941966
S.D.0.0378718707484808
T-STAT0.706971645842729
p-value0.518594022866628

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.22614773274332 \tabularnewline
beta & 0.0267743387941966 \tabularnewline
S.D. & 0.0378718707484808 \tabularnewline
T-STAT & 0.706971645842729 \tabularnewline
p-value & 0.518594022866628 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283599&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.22614773274332[/C][/ROW]
[ROW][C]beta[/C][C]0.0267743387941966[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0378718707484808[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.706971645842729[/C][/ROW]
[ROW][C]p-value[/C][C]0.518594022866628[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283599&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283599&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)
alpha-2.22614773274332
beta0.0267743387941966
S.D.0.0378718707484808
T-STAT0.706971645842729
p-value0.518594022866628






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-32.7678853727403
beta6.92751521594565
S.D.10.6072145434056
T-STAT0.653094663787338
p-value0.549331351666896
Lambda-5.92751521594565

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -32.7678853727403 \tabularnewline
beta & 6.92751521594565 \tabularnewline
S.D. & 10.6072145434056 \tabularnewline
T-STAT & 0.653094663787338 \tabularnewline
p-value & 0.549331351666896 \tabularnewline
Lambda & -5.92751521594565 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283599&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-32.7678853727403[/C][/ROW]
[ROW][C]beta[/C][C]6.92751521594565[/C][/ROW]
[ROW][C]S.D.[/C][C]10.6072145434056[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.653094663787338[/C][/ROW]
[ROW][C]p-value[/C][C]0.549331351666896[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.92751521594565[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283599&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283599&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-32.7678853727403
beta6.92751521594565
S.D.10.6072145434056
T-STAT0.653094663787338
p-value0.549331351666896
Lambda-5.92751521594565


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')