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 computationThu, 19 Aug 2010 21:01:47 +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/Aug/19/t1282251696nbwltysmmzex5fm.htm/, Retrieved Fri, 03 May 2024 13:07:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=79387, Retrieved Fri, 03 May 2024 13:07:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgilian keirsebelik
Estimated Impact134

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] [tijdreeks B-Stap 21] [2010-08-19 21:01:47] [46199ea7e385a69efb178ac615a86e3a] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
51
50
49
47
45
44
45
47
48
48
49
51
45
42
40
37
28
33
32
38
38
34
38
48
41
41
43
37
22
30
32
41
44
37
53
67
62
63
68
62
50
64
71
76
73
68
78
89
74
74
73
65
55
69
80
81
80
86
90
100
90
89
83
63
48
62
69
73
76
77
75
77
78
73
74
55
36
41
52
53
49
47
44
55

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79387&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79387&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79387&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
147.83333333333332.329000305762637
237.755.610461008444220
340.666666666666711.388457740052945
468.66666666666679.865765724632539
577.2511.825434837286545
673.511.866683690828842
754.7513.498316393333942

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 47.8333333333333 & 2.32900030576263 & 7 \tabularnewline
2 & 37.75 & 5.6104610084442 & 20 \tabularnewline
3 & 40.6666666666667 & 11.3884577400529 & 45 \tabularnewline
4 & 68.6666666666667 & 9.8657657246325 & 39 \tabularnewline
5 & 77.25 & 11.8254348372865 & 45 \tabularnewline
6 & 73.5 & 11.8666836908288 & 42 \tabularnewline
7 & 54.75 & 13.4983163933339 & 42 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79387&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]47.8333333333333[/C][C]2.32900030576263[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]37.75[/C][C]5.6104610084442[/C][C]20[/C][/ROW]
[ROW][C]3[/C][C]40.6666666666667[/C][C]11.3884577400529[/C][C]45[/C][/ROW]
[ROW][C]4[/C][C]68.6666666666667[/C][C]9.8657657246325[/C][C]39[/C][/ROW]
[ROW][C]5[/C][C]77.25[/C][C]11.8254348372865[/C][C]45[/C][/ROW]
[ROW][C]6[/C][C]73.5[/C][C]11.8666836908288[/C][C]42[/C][/ROW]
[ROW][C]7[/C][C]54.75[/C][C]13.4983163933339[/C][C]42[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79387&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79387&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
147.83333333333332.329000305762637
237.755.610461008444220
340.666666666666711.388457740052945
468.66666666666679.865765724632539
577.2511.825434837286545
673.511.866683690828842
754.7513.498316393333942






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.40251784874041
beta0.123787291802269
S.D.0.0976076325926626
T-STAT1.26821323818865
p-value0.260563795191672

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.40251784874041 \tabularnewline
beta & 0.123787291802269 \tabularnewline
S.D. & 0.0976076325926626 \tabularnewline
T-STAT & 1.26821323818865 \tabularnewline
p-value & 0.260563795191672 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79387&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.40251784874041[/C][/ROW]
[ROW][C]beta[/C][C]0.123787291802269[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0976076325926626[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.26821323818865[/C][/ROW]
[ROW][C]p-value[/C][C]0.260563795191672[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79387&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79387&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)
alpha2.40251784874041
beta0.123787291802269
S.D.0.0976076325926626
T-STAT1.26821323818865
p-value0.260563795191672






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.79821313926091
beta0.976684774008525
S.D.0.873262661965801
T-STAT1.11843184937039
p-value0.314218015379365
Lambda0.0233152259914747

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.79821313926091 \tabularnewline
beta & 0.976684774008525 \tabularnewline
S.D. & 0.873262661965801 \tabularnewline
T-STAT & 1.11843184937039 \tabularnewline
p-value & 0.314218015379365 \tabularnewline
Lambda & 0.0233152259914747 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79387&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.79821313926091[/C][/ROW]
[ROW][C]beta[/C][C]0.976684774008525[/C][/ROW]
[ROW][C]S.D.[/C][C]0.873262661965801[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11843184937039[/C][/ROW]
[ROW][C]p-value[/C][C]0.314218015379365[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0233152259914747[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79387&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79387&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-1.79821313926091
beta0.976684774008525
S.D.0.873262661965801
T-STAT1.11843184937039
p-value0.314218015379365
Lambda0.0233152259914747


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')