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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 computationWed, 29 Dec 2010 12:22:40 +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/29/t1293625217e9kge3y3oyimwqf.htm/, Retrieved Fri, 03 May 2024 09:56:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116746, Retrieved Fri, 03 May 2024 09:56:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact113

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...] [2010-12-29 12:22:40] [923770d86edf74ed976a539eae527e37] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98,4
96,5
97,4
99,2
100,8
101,8
102,7
100
100,8
101,7
99
101,7
100,2
101,2
99,5
100,8
100,7
99,5
99,4
101,1
97,2
98,1
97,8
95,5
96,3
93,6
96,7
95,1
97,7
96,5
98,1
97,3
97
93,7
95,6
94,6
95,1
94,5
93,6
92,1
95,9
98,1
98,2
96,2
94,1
95
93,4
95,4
93,5
94,5
94,3
95,7
98,4
99,4
99,2
99
99,4
99,3
98,6
98,7
96
98,7
100,1
100
101,5
101,5
103,8
104,1
101
104,9
104,4
105,6
103,4

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116746&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116746&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116746&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11001.925900025725876.2
299.251.770208000105185.7
396.01666666666671.50141347544324.5
495.13333333333331.810240231839336.10000000000001
597.52.287118075419175.9
6101.82.865151114529729.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100 & 1.92590002572587 & 6.2 \tabularnewline
2 & 99.25 & 1.77020800010518 & 5.7 \tabularnewline
3 & 96.0166666666667 & 1.5014134754432 & 4.5 \tabularnewline
4 & 95.1333333333333 & 1.81024023183933 & 6.10000000000001 \tabularnewline
5 & 97.5 & 2.28711807541917 & 5.9 \tabularnewline
6 & 101.8 & 2.86515111452972 & 9.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116746&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]100[/C][C]1.92590002572587[/C][C]6.2[/C][/ROW]
[ROW][C]2[/C][C]99.25[/C][C]1.77020800010518[/C][C]5.7[/C][/ROW]
[ROW][C]3[/C][C]96.0166666666667[/C][C]1.5014134754432[/C][C]4.5[/C][/ROW]
[ROW][C]4[/C][C]95.1333333333333[/C][C]1.81024023183933[/C][C]6.10000000000001[/C][/ROW]
[ROW][C]5[/C][C]97.5[/C][C]2.28711807541917[/C][C]5.9[/C][/ROW]
[ROW][C]6[/C][C]101.8[/C][C]2.86515111452972[/C][C]9.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116746&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116746&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
11001.925900025725876.2
299.251.770208000105185.7
396.01666666666671.50141347544324.5
495.13333333333331.810240231839336.10000000000001
597.52.287118075419175.9
6101.82.865151114529729.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-10.8923592864932
beta0.131446814722777
S.D.0.0695685632104522
T-STAT1.88945708602802
p-value0.131833156689535

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -10.8923592864932 \tabularnewline
beta & 0.131446814722777 \tabularnewline
S.D. & 0.0695685632104522 \tabularnewline
T-STAT & 1.88945708602802 \tabularnewline
p-value & 0.131833156689535 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116746&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.8923592864932[/C][/ROW]
[ROW][C]beta[/C][C]0.131446814722777[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0695685632104522[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.88945708602802[/C][/ROW]
[ROW][C]p-value[/C][C]0.131833156689535[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116746&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116746&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-10.8923592864932
beta0.131446814722777
S.D.0.0695685632104522
T-STAT1.88945708602802
p-value0.131833156689535






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-26.6117957287374
beta5.95001685892374
S.D.3.23748439998709
T-STAT1.83785190098444
p-value0.139946680959381
Lambda-4.95001685892374

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -26.6117957287374 \tabularnewline
beta & 5.95001685892374 \tabularnewline
S.D. & 3.23748439998709 \tabularnewline
T-STAT & 1.83785190098444 \tabularnewline
p-value & 0.139946680959381 \tabularnewline
Lambda & -4.95001685892374 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116746&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-26.6117957287374[/C][/ROW]
[ROW][C]beta[/C][C]5.95001685892374[/C][/ROW]
[ROW][C]S.D.[/C][C]3.23748439998709[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.83785190098444[/C][/ROW]
[ROW][C]p-value[/C][C]0.139946680959381[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.95001685892374[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116746&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116746&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-26.6117957287374
beta5.95001685892374
S.D.3.23748439998709
T-STAT1.83785190098444
p-value0.139946680959381
Lambda-4.95001685892374


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
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')