FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 21 Apr 2017 13:29:18 +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/2017/Apr/21/t1492777909ls6hvdy212bpk4f.htm/, Retrieved Sun, 12 May 2024 15:38:41 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 12 May 2024 15:38:41 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsOpdracht8_oefn2_stap3
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3.65
3.66
3.36
3.19
2.81
2.25
2.32
2.85
2.75
2.78
2.26
2.23
1.46
1.19
1.11
1
1.18
1.59
1.51
1.01
0.9
0.63
0.81
0.97
1.14
0.97
0.89
0.62
0.36
0.27
0.34
0.02
-0.12
0.09
-0.11
-0.38
-0.65
-0.4
-0.4
0.29
0.56
0.63
0.46
0.91
1.06
1.28
1.52
1.5
1.74
1.39
2.24
2.04
2.2
2.16
2.28
2.16
1.87
1.81
1.77
2.03
2.65

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=&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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
12.84250.5275177722124631.43
21.113333333333330.2908086947972790.96
30.3408333333333330.4786811110338551.52
40.5633333333333330.7441326046702522.17
51.974166666666670.2641094240628080.89

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.8425 & 0.527517772212463 & 1.43 \tabularnewline
2 & 1.11333333333333 & 0.290808694797279 & 0.96 \tabularnewline
3 & 0.340833333333333 & 0.478681111033855 & 1.52 \tabularnewline
4 & 0.563333333333333 & 0.744132604670252 & 2.17 \tabularnewline
5 & 1.97416666666667 & 0.264109424062808 & 0.89 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]2.8425[/C][C]0.527517772212463[/C][C]1.43[/C][/ROW]
[ROW][C]2[/C][C]1.11333333333333[/C][C]0.290808694797279[/C][C]0.96[/C][/ROW]
[ROW][C]3[/C][C]0.340833333333333[/C][C]0.478681111033855[/C][C]1.52[/C][/ROW]
[ROW][C]4[/C][C]0.563333333333333[/C][C]0.744132604670252[/C][C]2.17[/C][/ROW]
[ROW][C]5[/C][C]1.97416666666667[/C][C]0.264109424062808[/C][C]0.89[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
12.84250.5275177722124631.43
21.113333333333330.2908086947972790.96
30.3408333333333330.4786811110338551.52
40.5633333333333330.7441326046702522.17
51.974166666666670.2641094240628080.89






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.532076630487254
beta-0.0519644256543757
S.D.0.104437329500019
T-STAT-0.497565630059185
p-value0.652973902367952

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.532076630487254 \tabularnewline
beta & -0.0519644256543757 \tabularnewline
S.D. & 0.104437329500019 \tabularnewline
T-STAT & -0.497565630059185 \tabularnewline
p-value & 0.652973902367952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.532076630487254[/C][/ROW]
[ROW][C]beta[/C][C]-0.0519644256543757[/C][/ROW]
[ROW][C]S.D.[/C][C]0.104437329500019[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.497565630059185[/C][/ROW]
[ROW][C]p-value[/C][C]0.652973902367952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha0.532076630487254
beta-0.0519644256543757
S.D.0.104437329500019
T-STAT-0.497565630059185
p-value0.652973902367952






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.840621750236174
beta-0.193478047628016
S.D.0.262639872424557
T-STAT-0.736666698174672
p-value0.51470414885843
Lambda1.19347804762802

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.840621750236174 \tabularnewline
beta & -0.193478047628016 \tabularnewline
S.D. & 0.262639872424557 \tabularnewline
T-STAT & -0.736666698174672 \tabularnewline
p-value & 0.51470414885843 \tabularnewline
Lambda & 1.19347804762802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.840621750236174[/C][/ROW]
[ROW][C]beta[/C][C]-0.193478047628016[/C][/ROW]
[ROW][C]S.D.[/C][C]0.262639872424557[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.736666698174672[/C][/ROW]
[ROW][C]p-value[/C][C]0.51470414885843[/C][/ROW]
[ROW][C]Lambda[/C][C]1.19347804762802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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-0.840621750236174
beta-0.193478047628016
S.D.0.262639872424557
T-STAT-0.736666698174672
p-value0.51470414885843
Lambda1.19347804762802


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')