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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 computationThu, 26 Nov 2009 08:46:48 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/26/t1259250468h8ymzjech1qb7z9.htm/, Retrieved Sun, 28 Apr 2024 22:06:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60122, Retrieved Sun, 28 Apr 2024 22:06:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

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] [ws8 SMP] [2009-11-26 15:46:48] [8b8f95c5f2993a04d1b74eff1a82c018] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
89
88
86
89
84
86
85
86
85
83
85
84
88
84
84
86
85
88
87
88
87
89
90
94
95
95
96
97
97
97
96
100
97
98
96
94
95
93
95
96
96
98
95
96
98
94
93
94
92
92
93
95
92
94
96
97
95
94
96
93

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60122&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60122&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60122&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
185.83333333333331.946247360403816
287.52.7797972457128510
396.51.566698903601286
495.251.65831239517775
594.08333333333331.729862492345635

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 85.8333333333333 & 1.94624736040381 & 6 \tabularnewline
2 & 87.5 & 2.77979724571285 & 10 \tabularnewline
3 & 96.5 & 1.56669890360128 & 6 \tabularnewline
4 & 95.25 & 1.6583123951777 & 5 \tabularnewline
5 & 94.0833333333333 & 1.72986249234563 & 5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60122&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]85.8333333333333[/C][C]1.94624736040381[/C][C]6[/C][/ROW]
[ROW][C]2[/C][C]87.5[/C][C]2.77979724571285[/C][C]10[/C][/ROW]
[ROW][C]3[/C][C]96.5[/C][C]1.56669890360128[/C][C]6[/C][/ROW]
[ROW][C]4[/C][C]95.25[/C][C]1.6583123951777[/C][C]5[/C][/ROW]
[ROW][C]5[/C][C]94.0833333333333[/C][C]1.72986249234563[/C][C]5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60122&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60122&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
185.83333333333331.946247360403816
287.52.7797972457128510
396.51.566698903601286
495.251.65831239517775
594.08333333333331.729862492345635






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.68296274428341
beta-0.0734676486188947
S.D.0.0407409563325356
T-STAT-1.80328728710336
p-value0.169122438887294

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.68296274428341 \tabularnewline
beta & -0.0734676486188947 \tabularnewline
S.D. & 0.0407409563325356 \tabularnewline
T-STAT & -1.80328728710336 \tabularnewline
p-value & 0.169122438887294 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60122&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.68296274428341[/C][/ROW]
[ROW][C]beta[/C][C]-0.0734676486188947[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0407409563325356[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.80328728710336[/C][/ROW]
[ROW][C]p-value[/C][C]0.169122438887294[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60122&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60122&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)
alpha8.68296274428341
beta-0.0734676486188947
S.D.0.0407409563325356
T-STAT-1.80328728710336
p-value0.169122438887294






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha15.4059938133113
beta-3.26803468070402
S.D.1.62617594567172
T-STAT-2.00964396835553
p-value0.138030994345771
Lambda4.26803468070402

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 15.4059938133113 \tabularnewline
beta & -3.26803468070402 \tabularnewline
S.D. & 1.62617594567172 \tabularnewline
T-STAT & -2.00964396835553 \tabularnewline
p-value & 0.138030994345771 \tabularnewline
Lambda & 4.26803468070402 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60122&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15.4059938133113[/C][/ROW]
[ROW][C]beta[/C][C]-3.26803468070402[/C][/ROW]
[ROW][C]S.D.[/C][C]1.62617594567172[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.00964396835553[/C][/ROW]
[ROW][C]p-value[/C][C]0.138030994345771[/C][/ROW]
[ROW][C]Lambda[/C][C]4.26803468070402[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60122&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60122&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)
alpha15.4059938133113
beta-3.26803468070402
S.D.1.62617594567172
T-STAT-2.00964396835553
p-value0.138030994345771
Lambda4.26803468070402


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')